{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "importing Jupyter notebook from utils_common.ipynb\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.font_manager as mfm\n",
    "from matplotlib import cm\n",
    "from matplotlib import colors as mcolors\n",
    "from matplotlib.colors import rgb2hex\n",
    "import matplotlib.patches as mpatches\n",
    "import matplotlib.dates as mdates\n",
    "import time\n",
    "import datetime\n",
    "import seaborn as sns; sns.set()\n",
    "from matplotlib import rcParams\n",
    "rcParams.update({'figure.autolayout': True})\n",
    "import itertools\n",
    "from itertools import groupby\n",
    "from pyecharts.charts import Bar, Pie, Map, WordCloud, Geo\n",
    "from pyecharts import options as opts\n",
    "from snapshot_selenium import snapshot\n",
    "from pyecharts.render import make_snapshot\n",
    "from pyecharts.globals import ChartType, SymbolType\n",
    "from pyecharts.commons.utils import JsCode\n",
    "from pyecharts.globals import CurrentConfig, NotebookType\n",
    "CurrentConfig.NOTEBOOK_TYPE = NotebookType.JUPYTER_NOTEBOOK\n",
    "\n",
    "import import_ipynb\n",
    "from utils_common import *\n",
    "\n",
    "from pandas.plotting import register_matplotlib_converters\n",
    "register_matplotlib_converters()\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\", message=\"This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Where to save the dataframes and figures\n",
    "_Figure_PATH_ = './figures/'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# color palettes\n",
    "armyrose = ['#798234', '#a3ad62', '#d0d3a2', '#fdfbe4', '#f0c6c3', '#df91a3', '#d46780']\n",
    "tealrose = ['#009392', '#72aaa1', '#b1c7b3', '#f1eac8', '#e5b9ad', '#d98994', '#d0587e']\n",
    "geyser = ['#008080', '#70a494', '#b4c8a8', '#f6edbd', '#edbb8a', '#de8a5a', '#ca562c']\n",
    "earth = ['#A16928', '#bd925a', '#d6bd8d', '#edeac2', '#b5c8b8', '#79a7ac', '#2887a1']\n",
    "earth.reverse()\n",
    "fall = ['#3d5941', '#778868', '#b5b991', '#f6edbd', '#edbb8a', '#de8a5a', '#ca562c']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Figures"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# plot the confirmed cases\n",
    "def figure_conf(df, figsize = (8,5), fs = 15, logy = False, title = None, rank = 0):\n",
    "    \n",
    "    sns.set_style(\"whitegrid\")\n",
    "    palette = plt.get_cmap('magma')\n",
    "    \n",
    "    fig = plt.figure()\n",
    "    plot_df = df.groupby('update_date').agg('sum')\n",
    " \n",
    "    ax1 = fig.add_subplot(111)\n",
    "    plot_df.plot(y = ['cum_confirmed'], style = '-', marker = 'o', ax = ax1, \n",
    "                 figsize = figsize, logy = logy, color = palette(rank/50 + 0.2)) # grid = False, \n",
    "    ax1.set_ylabel(\"Number of people (cum)\", fontsize = fs - 2)\n",
    "    ax1.set_xticks([]) # hide the axes ticks\n",
    "    plt.legend(loc = 'upper left', fancybox = True, fontsize = fs - 2)\n",
    "    ax11 = ax1.twinx()\n",
    "    ax11.bar(x = plot_df.index, height = plot_df['new_confirmed'], color = palette(rank/50 + 0.2), alpha = 0.8)\n",
    "    \n",
    "    ax11.set_ylabel('Number of people (daily)', fontsize = fs - 2)\n",
    "    ax11.grid(False) # hide grid lines\n",
    "    \n",
    "    ax1.set_xlabel(\"Date\", fontsize = fs - 2)\n",
    "    \n",
    "    daily_patch = mpatches.Patch(color = palette(rank/50 + 0.2), label='daily_confirmed')\n",
    "    plt.legend(handles=[daily_patch], loc='upper left', bbox_to_anchor=(0, 0.9), fancybox=True, fontsize = fs - 2)\n",
    "\n",
    "    if title is not None:\n",
    "        fig.suptitle(title, fontsize = fs, y = 1)     \n",
    "    return fig\n",
    "    \n",
    "# plot the confirmed, the dead, and the cured cases\n",
    "def figure_conf_dead_cured(df, figsize=(10,8), fs=18, logy=False, title=None):\n",
    "    \n",
    "    sns.set_style(\"whitegrid\")\n",
    "    palette = [\"#50a3ba\", \"#eac763\", \"#d94e5d\"] # from pyecharts\n",
    "    #palette = [ '#79a7ac', '#bd925a', '#d98994'] # earth and tealrose\n",
    "    \n",
    "    fig = plt.figure()\n",
    "    plot_df = df.groupby('update_date').agg('sum')\n",
    " \n",
    "    ax1 = fig.add_subplot(211)\n",
    "    plot_df.plot(y = ['cum_confirmed'], style = '-', marker = 'o', ax = ax1, \n",
    "                 figsize = figsize, logy = logy, color = palette[2]) # grid = False, \n",
    "    ax1.set_ylabel(\"Number of people (cum)\", fontsize = fs - 2)\n",
    "    ax1.set_xticks([]) # hide the axes ticks\n",
    "    plt.legend(loc = 'upper left', fancybox = True, fontsize = fs - 4)\n",
    "    ax11 = ax1.twinx()\n",
    "    ax11.bar(x = plot_df.index, height = plot_df['new_confirmed'], color = palette[2], alpha = 0.8)\n",
    "    \n",
    "    ax11.set_ylabel('Number of people (new)', fontsize = fs - 2)\n",
    "    ax11.grid(False) # hide grid lines\n",
    "    \n",
    "    daily_patch = mpatches.Patch(color = palette[2], label='new_confirmed')\n",
    "    plt.legend(handles = [daily_patch], loc='upper left', bbox_to_anchor=(0, 0.9), fancybox = True, fontsize = fs - 4)\n",
    "    \n",
    "    ax2 = fig.add_subplot(212)\n",
    "    plot_df.plot(y = 'cum_cured', style = '-', marker = 'o', ax = ax2,\n",
    "                 figsize = figsize, sharex = False, logy = logy, color = palette[0])\n",
    "    plt.legend(loc = 'upper left', fancybox = True, fontsize = fs - 4)\n",
    "    ax22 = ax2.twinx()\n",
    "    plot_df.plot(y = 'cum_dead', style = '-', marker = 'o', ax = ax22,\n",
    "                 figsize = figsize, sharex = False, logy = logy, color = palette[1])\n",
    "    ax22.set_ylabel('Number of people dead', fontsize = fs - 2)\n",
    "    ax22.grid(False) # hide grid lines\n",
    "    \n",
    "    ax2.set_xlabel(\"Date\", fontsize = fs - 2)\n",
    "    ax2.set_ylabel(\"Number of people recovered\", fontsize = fs - 2)\n",
    "    \n",
    "    ax1.set_xlim(min(df.update_date), max(df.update_date))\n",
    "    ax1.xaxis.set_major_locator(mdates.WeekdayLocator())\n",
    "    ax1.xaxis.set_major_formatter(mdates.DateFormatter('%m-%d'))\n",
    "    \n",
    "    ax2.set_xlim(min(df.update_date), max(df.update_date))\n",
    "    ax2.xaxis.set_major_locator(mdates.WeekdayLocator())\n",
    "    ax2.xaxis.set_major_formatter(mdates.DateFormatter('%m-%d'))\n",
    "    \n",
    "    plt.legend(loc = 'upper left', bbox_to_anchor=(0, 0.9), fancybox = True, fontsize = fs - 4)\n",
    "    # align labels\n",
    "    ax1.get_yaxis().set_label_coords(-0.1,0.5)\n",
    "    ax2.get_yaxis().set_label_coords(-0.1,0.5)\n",
    "    ax11.get_yaxis().set_label_coords(1.1,0.5)\n",
    "    ax22.get_yaxis().set_label_coords(1.1,0.5)\n",
    "    \n",
    "    if title is not None:\n",
    "        fig.suptitle(title, fontsize = fs, y=1.01) \n",
    "    fig.savefig(_Figure_PATH_ + 'China_' + 'conf_cured_dead.png', dpi = 400, bbox_inches='tight')\n",
    "    return fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# plot the confirmed cases for every province\n",
    "def figure_conf_all(df, names_province, fsize = (5, 3), ncol = 3, ms = 2, fs = 10, logy = False, \n",
    "                    title = None, country = 'China'):\n",
    "    \n",
    "    sns.set_style(\"ticks\")\n",
    "    palette = plt.get_cmap('Reds')\n",
    "    \n",
    "    m = len(names_province)\n",
    "    \n",
    "    fig, axes = plt.subplots(int(np.ceil(m/ncol)), ncol, figsize = (2*fsize[0], int(np.ceil(m/ncol))*fsize[1]), sharey = False)\n",
    "    fig.subplots_adjust(hspace = 0.2, wspace = 0.1)\n",
    "    if m%ncol != 0:\n",
    "        for j in range(m, int(np.ceil(m/ncol)*ncol)):\n",
    "            fig.delaxes(axes.flatten()[j])\n",
    "    \n",
    "    df_rank = df[df['update_date'] == max(df['update_date'])].copy()\n",
    "    df_rank = df_rank.sort_values(by = 'province_name_en') # same order as the list names_province\n",
    "    df_rank = df_rank.reset_index(drop=True)\n",
    "    df_rank = df_rank.sort_values(by = 'cum_confirmed')\n",
    "    rank_list = df_rank.index.tolist()\n",
    "    \n",
    "    for i, province in enumerate(names_province):\n",
    "        \n",
    "        ix = np.unravel_index(i, axes.shape)\n",
    "        c = palette(rank_list.index(i)/2/m + 0.3)\n",
    "        \n",
    "        plot_df = df[df['province_name_en'] == province]\n",
    "        \n",
    "        axes[ix].plot(plot_df['update_date'], plot_df['cum_confirmed'],\n",
    "                linewidth = 2, marker = 'o', ms = ms, color = c, label = (lambda x: None if x > 0 else 'cum_confirmed')(i)) # \n",
    "        \n",
    "        if i >= (np.ceil(m/ncol) - 1)*ncol:\n",
    "            axes[ix].set_xlabel('Date', fontsize = fs - 2)\n",
    "            \n",
    "        if i % ncol == 0:\n",
    "            axes[ix].set_ylabel('Number (cum)', fontsize = fs - 2)\n",
    "            axes[ix].get_yaxis().set_label_coords(-0.15,0.5)\n",
    "        if i == 0:\n",
    "            axes[ix].legend(loc = 'upper left', fancybox = True, fontsize = fs - 4)\n",
    "        axes[ix].set_title(province, fontsize = fs)\n",
    "     \n",
    "    fig.align_ylabels(axes[:, 0])\n",
    "    \n",
    "    for i, province in enumerate(names_province):   \n",
    "        ix = np.unravel_index(i, axes.shape)\n",
    "        c = palette(rank_list.index(i)/2/m + 0.3)\n",
    "        \n",
    "        plot_df = df[df['province_name_en'] == province]\n",
    "        ax11 = axes[ix].twinx()\n",
    "        ax11.grid(False) # hide grid lines\n",
    "        ax11.bar(plot_df['update_date'], height = plot_df['new_confirmed'], color = c, alpha = 0.8,\n",
    "                label = (lambda x: None if x > 0 else 'new_confirmed')(i))\n",
    "        daily_patch = mpatches.Patch(color = c, label='new_confirmed')\n",
    "        if i == 0:\n",
    "            ax11.legend(handles=[daily_patch], loc='upper left', bbox_to_anchor=(0, 0.86), fancybox=True, fontsize = fs - 4)\n",
    "        ax11.tick_params(axis = 'both', which = 'major', labelsize = fs - 4)\n",
    "        ax11.tick_params(axis = 'both', which = 'minor', labelsize = fs - 4)\n",
    "        if i % ncol == ncol - 1:\n",
    "            ax11.set_ylabel('Number (new)', fontsize = fs - 2)\n",
    "            ax11.get_yaxis().set_label_coords(1.15,0.5)\n",
    "        \n",
    "        axes[ix].set_xlim(min(df.update_date), max(df.update_date))\n",
    "        axes[ix].xaxis.set_major_locator(mdates.WeekdayLocator())\n",
    "        axes[ix].xaxis.set_major_formatter(mdates.DateFormatter('%m-%d'))\n",
    "        axes[ix].tick_params(axis = 'both', which = 'major', labelsize = fs - 4)\n",
    "        axes[ix].tick_params(axis = 'both', which = 'minor', labelsize = fs - 4)\n",
    "        \n",
    "        \n",
    "    fig.align_ylabels(axes[:, 2])    \n",
    "    fig.suptitle(title, fontsize = fs + 2, y = 1.01)\n",
    "    \n",
    "    fig.savefig(_Figure_PATH_ + country + '_conf.png', dpi = 400, bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "🎄🎄🎄🎄🎄🎄🎄🎄🎄🎄🎄🎄🎄🎄🎄🎄🎄🎄🎄🎄🎄🎄🎄🎄🎄🎄🎄🎄🎄🎄🎄🎄🎄🎄🎄🎄🎄🎄🎄🎄🎄🎄🎄🎄"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# functions imported from utils_common\n",
    "data_city, data_province, data_province_domestic = load_DXY_raw()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# the date is truncated to March 10, 2020\n",
    "date_tr = datetime.date(int(2020),int(3),int(10))\n",
    "data_province_domestic = data_province_domestic[data_province_domestic.update_date <= date_tr]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(datetime.date(2020, 1, 15), datetime.date(2020, 3, 10))"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "min(data_province_domestic['update_date']), max(data_province_domestic['update_date'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>update_date</th>\n",
       "      <th>province_name</th>\n",
       "      <th>province_name_en</th>\n",
       "      <th>province_zip_code</th>\n",
       "      <th>cum_confirmed</th>\n",
       "      <th>cum_cured</th>\n",
       "      <th>cum_dead</th>\n",
       "      <th>new_confirmed</th>\n",
       "      <th>new_cured</th>\n",
       "      <th>new_dead</th>\n",
       "      <th>update_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-01-15</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>41.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-01-16</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>41.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-01-17</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>45.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-01-18</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>62.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-01-19</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>121.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2020-01-20</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>198.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2020-01-21</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>270.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>72.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2020-01-22</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>375.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>105.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2020-01-23</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>444.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2020-01-24</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>549.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>105.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2020-01-24 17:30:09.978000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2020-01-25</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>730.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>181.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>2020-01-25 23:55:35.775000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2020-01-26</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>1058.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>328.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>2020-01-26 13:50:35.848000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2020-01-27</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>1423.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>365.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>2020-01-27 16:42:57.343000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2020-01-28</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>2714.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>1291.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>2020-01-28 16:36:17.441000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2020-01-29</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>3554.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>125.0</td>\n",
       "      <td>840.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>2020-01-29 20:34:44.154000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>4903.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>162.0</td>\n",
       "      <td>1349.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>2020-01-30 22:24:37.371000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>5806.0</td>\n",
       "      <td>141.0</td>\n",
       "      <td>204.0</td>\n",
       "      <td>903.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>2020-01-31 22:06:41.473000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2020-02-01</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>7153.0</td>\n",
       "      <td>168.0</td>\n",
       "      <td>249.0</td>\n",
       "      <td>1347.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>2020-02-01 19:49:55.626000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2020-02-02</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>9074.0</td>\n",
       "      <td>267.0</td>\n",
       "      <td>294.0</td>\n",
       "      <td>1921.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>2020-02-02 20:50:05.247000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2020-02-03</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>11177.0</td>\n",
       "      <td>300.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>2103.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>2020-02-03 21:32:30.697000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2020-02-04</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>13522.0</td>\n",
       "      <td>397.0</td>\n",
       "      <td>414.0</td>\n",
       "      <td>2345.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>2020-02-04 17:34:45.960000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2020-02-05</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>16678.0</td>\n",
       "      <td>536.0</td>\n",
       "      <td>479.0</td>\n",
       "      <td>3156.0</td>\n",
       "      <td>139.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>2020-02-05 23:52:29.021000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2020-02-06</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>19665.0</td>\n",
       "      <td>712.0</td>\n",
       "      <td>549.0</td>\n",
       "      <td>2987.0</td>\n",
       "      <td>176.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>2020-02-06 20:28:31.381000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2020-02-07</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>22112.0</td>\n",
       "      <td>867.0</td>\n",
       "      <td>618.0</td>\n",
       "      <td>2447.0</td>\n",
       "      <td>155.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>2020-02-07 22:01:50.311000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2020-02-08</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>24953.0</td>\n",
       "      <td>1218.0</td>\n",
       "      <td>699.0</td>\n",
       "      <td>2841.0</td>\n",
       "      <td>351.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>2020-02-08 22:02:50.042000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2020-02-09</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>27100.0</td>\n",
       "      <td>1480.0</td>\n",
       "      <td>780.0</td>\n",
       "      <td>2147.0</td>\n",
       "      <td>262.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>2020-02-09 19:09:33.896000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2020-02-10</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>29631.0</td>\n",
       "      <td>1854.0</td>\n",
       "      <td>871.0</td>\n",
       "      <td>2531.0</td>\n",
       "      <td>374.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>2020-02-10 21:30:02.904000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2020-02-11</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>31728.0</td>\n",
       "      <td>2310.0</td>\n",
       "      <td>974.0</td>\n",
       "      <td>2097.0</td>\n",
       "      <td>456.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>2020-02-11 21:55:20.587000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2020-02-12</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>33366.0</td>\n",
       "      <td>2686.0</td>\n",
       "      <td>1068.0</td>\n",
       "      <td>1638.0</td>\n",
       "      <td>376.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>2020-02-12 22:07:03.407000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>48206.0</td>\n",
       "      <td>3459.0</td>\n",
       "      <td>1310.0</td>\n",
       "      <td>14840.0</td>\n",
       "      <td>773.0</td>\n",
       "      <td>242.0</td>\n",
       "      <td>2020-02-13 22:12:44.102000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>2020-02-14</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>51986.0</td>\n",
       "      <td>3900.0</td>\n",
       "      <td>1318.0</td>\n",
       "      <td>3780.0</td>\n",
       "      <td>441.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>2020-02-14 17:53:26.397000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>2020-02-15</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>54406.0</td>\n",
       "      <td>4821.0</td>\n",
       "      <td>1457.0</td>\n",
       "      <td>2420.0</td>\n",
       "      <td>921.0</td>\n",
       "      <td>139.0</td>\n",
       "      <td>2020-02-15 22:51:06.784000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>2020-02-16</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>56249.0</td>\n",
       "      <td>5666.0</td>\n",
       "      <td>1596.0</td>\n",
       "      <td>1843.0</td>\n",
       "      <td>845.0</td>\n",
       "      <td>139.0</td>\n",
       "      <td>2020-02-16 19:56:23.542000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>2020-02-17</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>58182.0</td>\n",
       "      <td>6693.0</td>\n",
       "      <td>1696.0</td>\n",
       "      <td>1933.0</td>\n",
       "      <td>1027.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>2020-02-17 20:22:59.982000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>2020-02-18</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>59989.0</td>\n",
       "      <td>7943.0</td>\n",
       "      <td>1789.0</td>\n",
       "      <td>1807.0</td>\n",
       "      <td>1250.0</td>\n",
       "      <td>93.0</td>\n",
       "      <td>2020-02-18 19:02:17.294000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>2020-02-19</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>61682.0</td>\n",
       "      <td>9336.0</td>\n",
       "      <td>1921.0</td>\n",
       "      <td>1693.0</td>\n",
       "      <td>1393.0</td>\n",
       "      <td>132.0</td>\n",
       "      <td>2020-02-19 21:47:42.544000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>2020-02-20</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>62031.0</td>\n",
       "      <td>10521.0</td>\n",
       "      <td>2029.0</td>\n",
       "      <td>349.0</td>\n",
       "      <td>1185.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>2020-02-20 22:08:31.581000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>2020-02-21</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>62662.0</td>\n",
       "      <td>11881.0</td>\n",
       "      <td>2144.0</td>\n",
       "      <td>631.0</td>\n",
       "      <td>1360.0</td>\n",
       "      <td>115.0</td>\n",
       "      <td>2020-02-21 20:57:17.698000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>2020-02-22</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>63454.0</td>\n",
       "      <td>13690.0</td>\n",
       "      <td>2250.0</td>\n",
       "      <td>792.0</td>\n",
       "      <td>1809.0</td>\n",
       "      <td>106.0</td>\n",
       "      <td>2020-02-22 20:55:28.727000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>2020-02-23</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>64084.0</td>\n",
       "      <td>15343.0</td>\n",
       "      <td>2346.0</td>\n",
       "      <td>630.0</td>\n",
       "      <td>1653.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>2020-02-23 20:06:03.658000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>2020-02-24</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>64287.0</td>\n",
       "      <td>16748.0</td>\n",
       "      <td>2495.0</td>\n",
       "      <td>203.0</td>\n",
       "      <td>1405.0</td>\n",
       "      <td>149.0</td>\n",
       "      <td>2020-02-24 19:12:21.027000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>2020-02-25</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>64786.0</td>\n",
       "      <td>18971.0</td>\n",
       "      <td>2563.0</td>\n",
       "      <td>499.0</td>\n",
       "      <td>2223.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>2020-02-25 23:14:30.774000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>2020-02-26</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>65187.0</td>\n",
       "      <td>20969.0</td>\n",
       "      <td>2615.0</td>\n",
       "      <td>401.0</td>\n",
       "      <td>1998.0</td>\n",
       "      <td>52.0</td>\n",
       "      <td>2020-02-26 22:07:00.782000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>2020-02-27</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>65596.0</td>\n",
       "      <td>23383.0</td>\n",
       "      <td>2641.0</td>\n",
       "      <td>409.0</td>\n",
       "      <td>2414.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>2020-02-27 20:07:32.954000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>2020-02-28</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>65914.0</td>\n",
       "      <td>26403.0</td>\n",
       "      <td>2682.0</td>\n",
       "      <td>318.0</td>\n",
       "      <td>3020.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>2020-02-28 08:35:31.270000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>2020-02-29</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>66337.0</td>\n",
       "      <td>28993.0</td>\n",
       "      <td>2727.0</td>\n",
       "      <td>423.0</td>\n",
       "      <td>2590.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>2020-02-29 20:08:01.693000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>2020-03-01</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>66907.0</td>\n",
       "      <td>31536.0</td>\n",
       "      <td>2761.0</td>\n",
       "      <td>570.0</td>\n",
       "      <td>2543.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>2020-03-01 18:06:02.378000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>2020-03-02</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>67103.0</td>\n",
       "      <td>33934.0</td>\n",
       "      <td>2803.0</td>\n",
       "      <td>196.0</td>\n",
       "      <td>2398.0</td>\n",
       "      <td>42.0</td>\n",
       "      <td>2020-03-02 23:05:02.252000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>2020-03-03</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>67217.0</td>\n",
       "      <td>36208.0</td>\n",
       "      <td>2835.0</td>\n",
       "      <td>114.0</td>\n",
       "      <td>2274.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>2020-03-03 19:41:02.494000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>2020-03-04</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>67332.0</td>\n",
       "      <td>38557.0</td>\n",
       "      <td>2871.0</td>\n",
       "      <td>115.0</td>\n",
       "      <td>2349.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>2020-03-04 21:50:02.887000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>2020-03-05</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>67466.0</td>\n",
       "      <td>40592.0</td>\n",
       "      <td>2902.0</td>\n",
       "      <td>134.0</td>\n",
       "      <td>2035.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>2020-03-05 22:51:01.569000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>2020-03-06</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>67592.0</td>\n",
       "      <td>42033.0</td>\n",
       "      <td>2931.0</td>\n",
       "      <td>126.0</td>\n",
       "      <td>1441.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>2020-03-06 23:09:02.356000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>2020-03-07</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>67666.0</td>\n",
       "      <td>43500.0</td>\n",
       "      <td>2959.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>1467.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>2020-03-07 19:19:01.632000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>2020-03-08</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>67707.0</td>\n",
       "      <td>45235.0</td>\n",
       "      <td>2986.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>1735.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>2020-03-08 22:39:16.068000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>2020-03-09</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>67743.0</td>\n",
       "      <td>46488.0</td>\n",
       "      <td>3008.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>1253.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>2020-03-09 22:17:01.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>2020-03-10</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>420000</td>\n",
       "      <td>67760.0</td>\n",
       "      <td>47743.0</td>\n",
       "      <td>3024.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>1255.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>2020-03-10 23:01:19.213000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   update_date province_name province_name_en  province_zip_code  \\\n",
       "0   2020-01-15           湖北省            Hubei             420000   \n",
       "1   2020-01-16           湖北省            Hubei             420000   \n",
       "2   2020-01-17           湖北省            Hubei             420000   \n",
       "3   2020-01-18           湖北省            Hubei             420000   \n",
       "4   2020-01-19           湖北省            Hubei             420000   \n",
       "5   2020-01-20           湖北省            Hubei             420000   \n",
       "6   2020-01-21           湖北省            Hubei             420000   \n",
       "7   2020-01-22           湖北省            Hubei             420000   \n",
       "8   2020-01-23           湖北省            Hubei             420000   \n",
       "9   2020-01-24           湖北省            Hubei             420000   \n",
       "10  2020-01-25           湖北省            Hubei             420000   \n",
       "11  2020-01-26           湖北省            Hubei             420000   \n",
       "12  2020-01-27           湖北省            Hubei             420000   \n",
       "13  2020-01-28           湖北省            Hubei             420000   \n",
       "14  2020-01-29           湖北省            Hubei             420000   \n",
       "15  2020-01-30           湖北省            Hubei             420000   \n",
       "16  2020-01-31           湖北省            Hubei             420000   \n",
       "17  2020-02-01           湖北省            Hubei             420000   \n",
       "18  2020-02-02           湖北省            Hubei             420000   \n",
       "19  2020-02-03           湖北省            Hubei             420000   \n",
       "20  2020-02-04           湖北省            Hubei             420000   \n",
       "21  2020-02-05           湖北省            Hubei             420000   \n",
       "22  2020-02-06           湖北省            Hubei             420000   \n",
       "23  2020-02-07           湖北省            Hubei             420000   \n",
       "24  2020-02-08           湖北省            Hubei             420000   \n",
       "25  2020-02-09           湖北省            Hubei             420000   \n",
       "26  2020-02-10           湖北省            Hubei             420000   \n",
       "27  2020-02-11           湖北省            Hubei             420000   \n",
       "28  2020-02-12           湖北省            Hubei             420000   \n",
       "29  2020-02-13           湖北省            Hubei             420000   \n",
       "30  2020-02-14           湖北省            Hubei             420000   \n",
       "31  2020-02-15           湖北省            Hubei             420000   \n",
       "32  2020-02-16           湖北省            Hubei             420000   \n",
       "33  2020-02-17           湖北省            Hubei             420000   \n",
       "34  2020-02-18           湖北省            Hubei             420000   \n",
       "35  2020-02-19           湖北省            Hubei             420000   \n",
       "36  2020-02-20           湖北省            Hubei             420000   \n",
       "37  2020-02-21           湖北省            Hubei             420000   \n",
       "38  2020-02-22           湖北省            Hubei             420000   \n",
       "39  2020-02-23           湖北省            Hubei             420000   \n",
       "40  2020-02-24           湖北省            Hubei             420000   \n",
       "41  2020-02-25           湖北省            Hubei             420000   \n",
       "42  2020-02-26           湖北省            Hubei             420000   \n",
       "43  2020-02-27           湖北省            Hubei             420000   \n",
       "44  2020-02-28           湖北省            Hubei             420000   \n",
       "45  2020-02-29           湖北省            Hubei             420000   \n",
       "46  2020-03-01           湖北省            Hubei             420000   \n",
       "47  2020-03-02           湖北省            Hubei             420000   \n",
       "48  2020-03-03           湖北省            Hubei             420000   \n",
       "49  2020-03-04           湖北省            Hubei             420000   \n",
       "50  2020-03-05           湖北省            Hubei             420000   \n",
       "51  2020-03-06           湖北省            Hubei             420000   \n",
       "52  2020-03-07           湖北省            Hubei             420000   \n",
       "53  2020-03-08           湖北省            Hubei             420000   \n",
       "54  2020-03-09           湖北省            Hubei             420000   \n",
       "55  2020-03-10           湖北省            Hubei             420000   \n",
       "\n",
       "    cum_confirmed  cum_cured  cum_dead  new_confirmed  new_cured  new_dead  \\\n",
       "0            41.0        7.0       1.0           41.0        7.0       1.0   \n",
       "1            41.0       12.0       2.0            0.0        5.0       1.0   \n",
       "2            45.0       15.0       2.0            4.0        3.0       0.0   \n",
       "3            62.0       19.0       2.0           17.0        4.0       0.0   \n",
       "4           121.0       24.0       3.0           59.0        5.0       1.0   \n",
       "5           198.0       25.0       3.0           77.0        1.0       0.0   \n",
       "6           270.0       25.0       6.0           72.0        0.0       3.0   \n",
       "7           375.0       28.0       9.0          105.0        3.0       3.0   \n",
       "8           444.0       28.0      17.0           69.0        0.0       8.0   \n",
       "9           549.0       31.0      24.0          105.0        3.0       7.0   \n",
       "10          730.0       32.0      39.0          181.0        1.0      15.0   \n",
       "11         1058.0       42.0      52.0          328.0       10.0      13.0   \n",
       "12         1423.0       47.0      76.0          365.0        5.0      24.0   \n",
       "13         2714.0       52.0     100.0         1291.0        5.0      24.0   \n",
       "14         3554.0       87.0     125.0          840.0       35.0      25.0   \n",
       "15         4903.0       90.0     162.0         1349.0        3.0      37.0   \n",
       "16         5806.0      141.0     204.0          903.0       51.0      42.0   \n",
       "17         7153.0      168.0     249.0         1347.0       27.0      45.0   \n",
       "18         9074.0      267.0     294.0         1921.0       99.0      45.0   \n",
       "19        11177.0      300.0     350.0         2103.0       33.0      56.0   \n",
       "20        13522.0      397.0     414.0         2345.0       97.0      64.0   \n",
       "21        16678.0      536.0     479.0         3156.0      139.0      65.0   \n",
       "22        19665.0      712.0     549.0         2987.0      176.0      70.0   \n",
       "23        22112.0      867.0     618.0         2447.0      155.0      69.0   \n",
       "24        24953.0     1218.0     699.0         2841.0      351.0      81.0   \n",
       "25        27100.0     1480.0     780.0         2147.0      262.0      81.0   \n",
       "26        29631.0     1854.0     871.0         2531.0      374.0      91.0   \n",
       "27        31728.0     2310.0     974.0         2097.0      456.0     103.0   \n",
       "28        33366.0     2686.0    1068.0         1638.0      376.0      94.0   \n",
       "29        48206.0     3459.0    1310.0        14840.0      773.0     242.0   \n",
       "30        51986.0     3900.0    1318.0         3780.0      441.0       8.0   \n",
       "31        54406.0     4821.0    1457.0         2420.0      921.0     139.0   \n",
       "32        56249.0     5666.0    1596.0         1843.0      845.0     139.0   \n",
       "33        58182.0     6693.0    1696.0         1933.0     1027.0     100.0   \n",
       "34        59989.0     7943.0    1789.0         1807.0     1250.0      93.0   \n",
       "35        61682.0     9336.0    1921.0         1693.0     1393.0     132.0   \n",
       "36        62031.0    10521.0    2029.0          349.0     1185.0     108.0   \n",
       "37        62662.0    11881.0    2144.0          631.0     1360.0     115.0   \n",
       "38        63454.0    13690.0    2250.0          792.0     1809.0     106.0   \n",
       "39        64084.0    15343.0    2346.0          630.0     1653.0      96.0   \n",
       "40        64287.0    16748.0    2495.0          203.0     1405.0     149.0   \n",
       "41        64786.0    18971.0    2563.0          499.0     2223.0      68.0   \n",
       "42        65187.0    20969.0    2615.0          401.0     1998.0      52.0   \n",
       "43        65596.0    23383.0    2641.0          409.0     2414.0      26.0   \n",
       "44        65914.0    26403.0    2682.0          318.0     3020.0      41.0   \n",
       "45        66337.0    28993.0    2727.0          423.0     2590.0      45.0   \n",
       "46        66907.0    31536.0    2761.0          570.0     2543.0      34.0   \n",
       "47        67103.0    33934.0    2803.0          196.0     2398.0      42.0   \n",
       "48        67217.0    36208.0    2835.0          114.0     2274.0      32.0   \n",
       "49        67332.0    38557.0    2871.0          115.0     2349.0      36.0   \n",
       "50        67466.0    40592.0    2902.0          134.0     2035.0      31.0   \n",
       "51        67592.0    42033.0    2931.0          126.0     1441.0      29.0   \n",
       "52        67666.0    43500.0    2959.0           74.0     1467.0      28.0   \n",
       "53        67707.0    45235.0    2986.0           41.0     1735.0      27.0   \n",
       "54        67743.0    46488.0    3008.0           36.0     1253.0      22.0   \n",
       "55        67760.0    47743.0    3024.0           17.0     1255.0      16.0   \n",
       "\n",
       "                   update_time  \n",
       "0                          NaN  \n",
       "1                          NaN  \n",
       "2                          NaN  \n",
       "3                          NaN  \n",
       "4                          NaN  \n",
       "5                          NaN  \n",
       "6                          NaN  \n",
       "7                          NaN  \n",
       "8                          NaN  \n",
       "9   2020-01-24 17:30:09.978000  \n",
       "10  2020-01-25 23:55:35.775000  \n",
       "11  2020-01-26 13:50:35.848000  \n",
       "12  2020-01-27 16:42:57.343000  \n",
       "13  2020-01-28 16:36:17.441000  \n",
       "14  2020-01-29 20:34:44.154000  \n",
       "15  2020-01-30 22:24:37.371000  \n",
       "16  2020-01-31 22:06:41.473000  \n",
       "17  2020-02-01 19:49:55.626000  \n",
       "18  2020-02-02 20:50:05.247000  \n",
       "19  2020-02-03 21:32:30.697000  \n",
       "20  2020-02-04 17:34:45.960000  \n",
       "21  2020-02-05 23:52:29.021000  \n",
       "22  2020-02-06 20:28:31.381000  \n",
       "23  2020-02-07 22:01:50.311000  \n",
       "24  2020-02-08 22:02:50.042000  \n",
       "25  2020-02-09 19:09:33.896000  \n",
       "26  2020-02-10 21:30:02.904000  \n",
       "27  2020-02-11 21:55:20.587000  \n",
       "28  2020-02-12 22:07:03.407000  \n",
       "29  2020-02-13 22:12:44.102000  \n",
       "30  2020-02-14 17:53:26.397000  \n",
       "31  2020-02-15 22:51:06.784000  \n",
       "32  2020-02-16 19:56:23.542000  \n",
       "33  2020-02-17 20:22:59.982000  \n",
       "34  2020-02-18 19:02:17.294000  \n",
       "35  2020-02-19 21:47:42.544000  \n",
       "36  2020-02-20 22:08:31.581000  \n",
       "37  2020-02-21 20:57:17.698000  \n",
       "38  2020-02-22 20:55:28.727000  \n",
       "39  2020-02-23 20:06:03.658000  \n",
       "40  2020-02-24 19:12:21.027000  \n",
       "41  2020-02-25 23:14:30.774000  \n",
       "42  2020-02-26 22:07:00.782000  \n",
       "43  2020-02-27 20:07:32.954000  \n",
       "44  2020-02-28 08:35:31.270000  \n",
       "45  2020-02-29 20:08:01.693000  \n",
       "46  2020-03-01 18:06:02.378000  \n",
       "47  2020-03-02 23:05:02.252000  \n",
       "48  2020-03-03 19:41:02.494000  \n",
       "49  2020-03-04 21:50:02.887000  \n",
       "50  2020-03-05 22:51:01.569000  \n",
       "51  2020-03-06 23:09:02.356000  \n",
       "52  2020-03-07 19:19:01.632000  \n",
       "53  2020-03-08 22:39:16.068000  \n",
       "54  2020-03-09 22:17:01.250000  \n",
       "55  2020-03-10 23:01:19.213000  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_slice = data_province_domestic[data_province_domestic['update_date'] == datetime.date(int(2020),int(1),int(31))]\n",
    "data_slice = data_slice.sort_values(by = 'province_name_en')\n",
    "data_slice = data_province_domestic[data_province_domestic['province_name_en'] == 'Hubei']\n",
    "data_slice = data_slice.reset_index(drop = True)\n",
    "data_slice"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x1440 with 60 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "figure_conf_all(df = data_province_domestic, names_province = names_province, \n",
    "                fsize = (7, 2), ncol = 3, ms = 3, fs = 12, logy = False, \n",
    "                title = 'China: infection', country = 'China')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x504 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = figure_conf_dead_cured(data_province_domestic, figsize = (10, 7), fs = 16, logy = False, title = 'China: confirmed, cured, and dead')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "#province = 'Hubei'   # target province\n",
    "#fig = figure_conf_dead_cured(data_province[data_province['province_name_en'] == province], title = province + ': confirmed, cured, and dead')\n",
    "#plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "#city = 'Wuhan' # target city\n",
    "#fig = figure_conf_dead_cured(data_city[data_city['city_name_en'] == city], logy = False, title = city + ': confirmed, cured, and dead')\n",
    "#plt.show()  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# plot a specific column: confirmed, cured or dead\n",
    "def figure_bar(df, date_str, col, largestN = 0, log = True, figsize = (12, 8), fs = 18, title = None):\n",
    "    \n",
    "    sns.set_style(\"whitegrid\")\n",
    "    year, month, day = date_str.split('-')\n",
    "    \n",
    "    date = datetime.date(int(year),int(month),int(day))\n",
    "    if date_str is not None:\n",
    "        df_single = df[df['update_date'] == date]\n",
    "    else:\n",
    "        df_single = df\n",
    "        \n",
    "    df_single = df_single[df_single['province_name_en'].isin(names_province)]\n",
    "    df_single = df_single.sort_values(by = col)\n",
    "    df_single = df_single.reset_index(drop = True)\n",
    "        \n",
    "    if largestN > 0:\n",
    "        df_single = df_single[-largestN:]  # only plot the first N bars\n",
    "    else:\n",
    "        largestN = df_single.shape[0]\n",
    "    \n",
    "    cmap_dict = {'cum_confirmed': tealrose, 'new_confirmed': tealrose, \n",
    "                 'cum_cured': armyrose, 'new_cured': armyrose, \n",
    "                 'cum_dead': earth, 'new_dead': earth,\n",
    "                 'infection_rate': tealrose}\n",
    "    \n",
    "    palette = cmap_dict[col]\n",
    "    palette = list(itertools.chain.from_iterable(itertools.repeat(x, int(np.ceil(largestN/len(palette)))) for x in palette))\n",
    "    palette = palette[:largestN]\n",
    "    \n",
    "    \n",
    "    fig = plt.figure(figsize = figsize)\n",
    "    ax = fig.add_subplot(111)\n",
    "    bars = df_single[col].tolist()\n",
    "    # in case zero appears\n",
    "    bars = [temp if temp > 0 else 0.1 for temp in bars]\n",
    "    names = df_single['province_name_en']\n",
    "    ax.barh(names, bars, color = palette, height = 0.4, alpha = 0.8) # palette(np.linspace(0.2, 0.8, largestN))    \n",
    "    for j, v in enumerate(bars): # add text\n",
    "        ax.text(v*1.1, j - 0.2, str(int(v)), color = 'black', fontsize = fs - 6)\n",
    "    ax.set_xlabel(\"Number of people\", fontsize = fs - 2)\n",
    "    ax.set_ylabel('Province', fontsize = fs - 2)\n",
    "    if log == True:\n",
    "        ax.set_xscale('log')\n",
    "        xmin = np.power(10, np.floor(np.log10(min(bars))))\n",
    "        xmax = np.power(10, np.ceil(np.log10(max(bars))))\n",
    "        ax.set_xlim(xmin, xmax)\n",
    "    \n",
    "    if title is not None:\n",
    "        fig.suptitle(title + ' ' + col[:3] + ' ' + col[4:], fontsize = fs, y = (lambda x: 1.06 if x != len(names_province) else 1.035)(largestN))\n",
    "    plt.figtext(0.5, 1, date.strftime(\"%d %B, %Y\"), ha = \"center\", va = \"top\", fontsize = fs - 4)\n",
    "    if largestN != len(names_province):\n",
    "        fig.savefig(_Figure_PATH_ + 'figures_china/' + 'China_bar_' + col[4:] + '_top.png', dpi = 400, bbox_inches='tight')\n",
    "    else:\n",
    "        fig.savefig(_Figure_PATH_ + 'figures_china_be/' 'China_bar_' + col[4:] + '.png', dpi = 400, bbox_inches='tight')\n",
    "    return fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 241,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = figure_bar(df = data_province_domestic, date_str = '2020-03-10', \n",
    "                 col = 'cum_confirmed', largestN = 10, log = True, figsize = (6, 4), fs = 15, \n",
    "                 title = 'China: provincial')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 244,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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MCSHEq8g9JCGEEDpBCpIQQgidIEN2QgghdIJcIQkhhNAJUpCEEELoBClIQgghdIIUJCGEEDpBCpIQQgidIAVJ5ApqtZqRI0dqpKmqVComT55M69at+eyzz/jtt98y3TYoKAhLS0uCg4M1lickJGBra8vXX3/9ztppaWmZYcLWV0lNTWX69Om0a9cOV1dXfH19lX0kJiYydOhQ2rRpQ6tWrTTSZf/88088PT1xc3PDw8NDIwRx48aNtG3bls8//5xx48aRnJz8bk5QiPdICpLQedeuXcPb25tdu3ZpLF+7di2RkZFs27aNjRs38uuvv2YZ212mTBm2bNmisWz37t0ULFjwvbU7u4KDgzl37hybNm0iNDSU8uXLM3XqVCCtmBYsWJAdO3bwyy+/MGHCBKKjo3ny5AnDhg1j2rRpbNmyhSlTpjB48GCePn3K5cuXCQoKYtWqVezcuZMnT55oxMELoaukIAmdt3r1ajp16pRhOqK9e/fi6emJoaEhRYoUoV27dmzdujXTfTRu3JirV68qCb0AmzZton379srPN27c4Msvv6Rz5840b96cb7/9lufPnwNpwXCDBg2iVatWnDlzhlOnTtGpUydcXFzw8PDQmEE6KCgIT09PnJ2dWb169SvPr0qVKowYMQJjY2PlWLdv31bOsVOnTkBaUW3UqBE7duwgOTmZcePGUbVqVWUfarWamJgY9u3bh7OzMxYWFujr69OlS5cs+0UIXSIFSei877//PtP4jTt37igBh5CWVvpiwXmRoaEhbdq0Ud6Yb9++TXx8vPKGDrB+/Xrc3d1Zv349u3fvJioqirCwMACSk5Np3rw5u3btonr16vTv35/+/fuzbds2fvjhBwICApQYi3LlyhESEsK8efOYOnXqK4fLbG1tsbKyAtKC8xYsWKAU35fPsWTJkkRHR2NhYUHbtm2V5XPnzqVChQqUK1cu0365e/eu1jYIoQukIIlcS61Wa8yCrlarNdJLX+bm5kZoaCiQljPl7u6u8Xr6bNFLlixh/Pjx3Lt3TyMcr169egBcvnwZfX19mjVrBqRd0YSGhirHdnFxAdIiwZOSkpTE21e5efMmX3zxBXZ2dvTo0SPTcwQ0zjElJYVJkyaxc+dOgoKClG1e9Kp+EUJXyG+pyLVKly6tEWZ37949rdEItWvXRqVSceHCBbZv364UjnTfffcd69ev55NPPqFXr15YWVlpvLmn328yMDDIUCQuX75MSkoKkHY1BijrZGd2rqNHj9KlSxfc3d2ZOHGisq22c4yNjaVPnz5cvnyZdevWUaZMmTfqFyF0hRQkkWu1aNGC4OBgUlJSiIuL4/fff6dly5Zat3FzcyMgIECJtH7RoUOH6N+/vzIUdurUqQzJsQCVKlVCT0+Pw4cPA3Du3Dm8vb0zRI9n17lz5/D19WXatGn06dMnwzmuW7cOgOjoaP7880+aN2+OSqWiX79+lC1blp9//hlzc3NlG2dnZ/bv38/Dhw9Rq9WsW7fulf0ihC6QgD6Ra3Xr1o2bN2/i5uZGcnIyXbp0wd7eXus27du3JzAwkAULFmR4bciQIfTv35+CBQtiYmJC/fr1M423NjY2JigoiICAAKZPn46RkRFBQUHKQwlZcXNzY9KkSUoYX7pZs2ahVquZOXMmM2fOBKBs2bLMnz+fAQMGMH78eNq1a4dKpWL48OGUL1+ebdu2cfLkSRISEjTShKdPn67c4/L29iY5ORkbGxv69u2rtW1C6AKZ7VuID2T27Nm0b9+eypUr53RThNBJMmQnxAegVqv55JNPpBgJoYVcIQkhhNAJcoUkhBBCJ0hBEkIIoROkIAkhhNAJUpCEEELoBClIQgghdIIUJCGEEDpBZmrIRVJTU4mPj8fIyCjDXGpCCPG+qNVqkpOTKVSo0HudqFcKUi4SHx/P5cuXc7oZQog8qlq1ahQuXPi97V8KUi5iZGQEpP1SvGretLzo7NmzWFtb53QzdJb0j3bSP1lLSkri8uXLynvQ+yIFKRdJH6YzNjYmX758Odwa3ST9op30j3bSP9q971sF8lCDEEIInSAFSQghhE6QgiSEEEInSEESQgihE6QgCSGE0AlSkIQQQugEKUhCCCF0ghQkIYQQOkEKkhBCCJ0gBUkIIYROkIIkhBBCJ0hBEkIIoROkIAkhhNAJUpCEEELoBClIQgghdIIUJCGEEDpBCpIQQgidIAVJCCGETpCCJIQQQifoqdVqdU43QhdFRUXRs2dP9u/fr7Hc0tKSS5cuZbpNeHg48+bNY+XKldk+Tt++fZk0aRIlS5Z85brPnz/n7Nmz1KhcBWNj42wfI69ISkqSftFC+ke7vNY/evr6GOTPp/w8ZcoUtm7dSlJSEj4+PuzZs4fo6GgAbty4gaWlJQMGDGDmzJkAqNVqDh06xNmzZylatCh9+/YlJiYGlUrFihUrqFy5MkuWLGHx4sUYGhri7++Pi4uL1jYZvr/TFdmxZMmS194mevs+DJJT3kNrcreEhAQKFiyY083QWdI/2uW1/vmkk6vy97CwMP766y8OHz5MQkICM2bMYO3atQDExMTQrFkzhg4dSrNmzXB1Tdvuxx9/pFGjRtSoUYNevXrRo0cPOnfuzB9//MHFixcpVKgQc+fOJSIigmfPnuHk5MRnn31Gvnz5Mm0PyJDdGwkJCcHPz0/52cvLi/DwcCDtH69Pnz64uroyZswYkpKSADh48CAdO3bE3d0dX19fYmJiAHB2diYqKurDn4QQQvy/Xbt2UatWLTw8PHB1ddW4khk3bhzffvstxYoVU5ZFRUWxcuVKxo0bB8Dhw4eJioqiZcuWrF69mmbNmnHs2DEaNWpEvnz5KFKkCFWqVOH06dNa2yEFSYt79+7h5uam8edVoqKiGDt2LFu3biU+Pp7ffvuNR48eMXPmTJYtW8bmzZtxcnJixowZH+AMhBDi1R48eEBERAQbNmxg0aJF9OjRA7Vazb1799i3bx89e/bUWH/WrFkMGTJEudqJjIzE3NycvXv3Ur58eaZNm0ZcXBxFihRRtilcuDCxsbFa2yFDdlqUKFGCLVu2aCyztLTUuk29evWoUKECAK6uroSEhFC+fHnu3Lmj/KOmpqZq/EO9rsTERPSTkt94+49ZQkJCTjdBp0n/aJeX+icpKYlTF84DkJycjJWVFWfOnAHS7g/t3buXffv20bRpUy5cuKBsl5qayrZt25g8ebKyrGjRorRv3x5AGR2qV68eT548UdZ58uQJZmZmWtskBekN6Onp8eKzIMnJ/ysOhob/61K1Wo2hoSEqlQo7OzsWLVoEpD2cEB8f/8bHL1CgAAaGRm+8/ccqr90DeF3SP9rltf4xNjambt26AHTs2JE5c+ZgZ2fHnTt3SE1NxdnZmYULF+Lv74+VlRVnz54F4OzZs1SvXp0CBQoo+3JycmL79u14eXlx8OBBrKyssLe3Z8yYMTx79oznz59z4cIFrK2ttbZJCtIbMDc359q1a6jVaqKiojSeujt+/Di3b9+mVKlSbN68mcaNG2NjY4O/vz83btygYsWKLFiwgLt37zJ16tQcPAshhEjj4uLCwYMHsbe3JzU1lfnz52NgYMClS5eoVKmSxrqZLZs5cyZfffUVCxcupEiRIqxZswZzc3MGDhxI48aNSU1NZfLkyeTPn19rO+Sx7yxoe+z7zJkzDB06lMuXL1OxYkVSUlLo27cvAIGBgeTLl4/79+/j4ODA6NGjMTAwYP/+/cyZM4fU1FRKlizJjz/+iLm5Oc7OzqxYsYKyZcu+sk3y2Ld2ee2x3dcl/aNdXuuflx/71ib9vcfa2lrrU3Jv3SYpSLnHh/qlyK2OHz+uDEGIjKR/tJP+ydqHeu+Rp+yEEELoBClIQgghdIIUJCGEEDpBCpIQQgidIAVJCCGETpCCJIQQQidIQRJCCKETcs1MDSkpKSxZsoStW7eip6eHSqXCw8ODr7/+Gj09vQ/alqCgIAAGDBjwQY+bTpX4jBRVao4cW5fVqFyFlITEnG6Gzspu/2T2hcnw8HBGjhxJWFgY58+fp1+/fqjVamxsbAgKCsLAwICBAwdy+PBhChcuDMCWLVtITEykR48eJCUlUbp0aZYvX56npucRryfXFKQJEybw4MED1q1bh6mpKU+fPqV///4ULlyYHj165HTzPijJQ8pcXpuL7HVlt39ezMkBmD59OitXrqRQoUIAjB49moCAAJo0aUKvXr3YunUrHh4e/PPPP+zatUsjpmDcuHF4e3vTs2dPxo8fz+LFixkyZMi7PTHx0cgVBSk6OpqtW7dy8OBBTE1NATAxMeH777/n6tWr+Pn5YW9vj6enJ/C/VNe7d+8yevRonjx5wr179/Dw8GDQoEGEhITw559/Ehsby61bt2jUqBHjx48H0uZk2rVrF+bm5hQvXhxnZ2c8PT1ZunQp69evx9zcHFNTU2rXrg3AH3/8QWBgIKmpqZQrV46JEydSrFgxnJ2dad++PYcOHSIxMZFp06ZhbW3N5cuX8fPzQ6VSUa9ePQ4ePMiePXtypF+FyI7KlSsTEhKCl5cXAMHBwRgYGJCUlER0dDQlS5YkNTWVK1eu0K9fP+7evUufPn3o3bs3s2fPRq1Wk5qayq1bt6hWrVoOn43QZbmiIJ0+fZrKlStniGyoXLkylStX5o8//sh0u23btuHi4oKHhwdPnjyhadOmyn+qEydOsG3bNgwMDGjdujXdunXjv//+4/jx42zbto3ExEQ8PDxwdnbmzJkzBAcHs2nTJvT09OjSpQu1a9fm4cOHfP/99/z222+ULVuWpUuXMnHiRObOnQuAmZkZGzduZOXKlSxevJigoCD8/PwYNGgQTZs2Zfny5ahUqtfuD4mfyFpeig94E9npnxdjCQAqVKjAxYsXiY+P5/jx4wDcuXMHHx8fTExMSExM5NChQ3h6evLFF1+gUqn45ptvKFiwIFWrViUlJYVu3bqRlJSEh4eHsg9dpMttywtyRUECNO4T7dy5k4ULF5KamoqxsTFVq1bNdJs+ffpw9OhRli1bxpUrV0hOTiYxMW0M3dbWFhMTEwDKlStHbGwsf/31F23atMHY2BhjY2NatmwJwLFjx2jatKkyZNG6dWtSU1M5ffo0tWvXViZG7dKlCz/99JNy/MaNGwNQtWpVdu/ezePHj/nvv/9o2rQpAB06dGDFihWv3RcSP5E5GbLTLrv982IsQbqiRYtSqFAhjeUuLi4sXbqUFStW8PPPP2Nra6vcP3JxcSE5OVlZ//r16+zdu5cffviBAwcOvMOzendkLruspc9l977liqfsrK2tuXbtGk+fPgXSCsKWLVtYuHAhMTExGvlEL2YTTZ06lZUrV1KmTBm+/fZbzM3NlfVenCAwfXt9fX1SUzM+LPBy/lF65tHL66rValJS/ndvJ/0Y6cXUwMAAmctW5Hbt27fnypUrQFoKqL6+PpcvX8bJyQmVSkVycjKHDh3Czs4OHx8fZQQjfV0hspIrrpDKlClD+/btGTlyJFOmTMHU1JSUlBTCwsLQ19fHzMyMq1evArB3715lu8OHDzNhwgTs7OwICwvj7t27mRacdA0bNmTJkiXK8EJYWBg1atTA0dGRQYMG4evri7GxMXv27KFp06bY2Ngwbtw4oqKiKFu2LOvWraNBgwZZ7r9w4cKUK1eOAwcO0LRpU0JDQ9+oP0q1bZGnpsnPrrwWH/C6sts/eq8oGn5+fvTq1QtjY2MKFizI0qVLKV26ND169MDBwQEjIyN69uyJlZUVAwcO5JtvvmHixIno6+uzYMGCd3U64iOUKwoSwPjx4/nll1/o2bMnKpWK+Ph4GjRowJIlSzAwMGDw4MG4urri4OBA8eLFAfj6668ZMWIE+fPnp1SpUlhbWxMVFZXlMZo1a8aJEyfw8PCgSJEilChRgnz58lGjRg28vb3p2LEjpqamlClTBoBixYoxceJEfH19SU5OpkyZMhqxvpmZPn06o0ePJjAwEEtLy1cGVmXGoEB+DCV+IoNTF87LkIsWb9M/FSpU4OjRo0DaB7fDhw9nWGfEiBGMGDFCY1n16tUJCwt7o2OKvEfykF5w4sQJIiMj8fDwIDk5mS5duhAQEED16tXf2THmzZtH586dKVGiBLt37yZsecezAAAgAElEQVQ0NFT5XtOrSB6SdnIPQDvpH+2kf7L2od57cs0V0odQsWJF5s2bxy+//IJarcbd3f2dFiNIG37s3bs3hoaGmJqavvKKSggh8gopSC8wMzNj2bJl7/UYnp6eyvelhBBC/I888iKEEEInSEESQgihE6QgCSGE0AlSkIQQQugEeajhBVFRUfTs2ZP9+/drLE+frFVXSPxE5iR+QrtX9c+rYidOnjzJgAEDMDAwIF++fKxYsYI7d+4wePBgZf2jR4+yefNmatasSe/evUlJSUGtVvPTTz9haWn53s5NfBykIOVCEj+ROZnLTrtX9c+rYicGDRpEUFAQderUYfHixUybNo1Zs2YpX3zdsGEDZcqUoXXr1nh7e+Pr64u7uzu7du1i1KhRhISEvLdzEx8HKUjZpFKpmD59OseOHUOlUuHp6UmvXr0IDw9n8eLF5M+fn2vXrmFpacmMGTMwNjZm9uzZHDlyhNjYWEqUKMHs2bMpVqwYTk5OtGrViuPHj2NgYEBgYCDlypXL6VMUQsPLsRNr166ldOnSQFpg5ouzjMTHxzNu3DgOHjwIpMW4pM/O//K6QmRFCtJL7t27h5ubW4bl69evB2DTpk0kJSXRp08frK2tgbQZHnbs2EGJEiXo3Lkzhw4donLlyly/fp21a9eir6/PiBEj2Lp1K7179+b+/fs4OjoyduxYpk6dyurVq/Hz88t2GyV+ImsSP6Gdtv7JTuzE7du3OXXqFDNmzGDJkiXK8rVr1+Lk5MS///7Lv//+q+wjMjKSYcOGMWPGjFwR7ZAb2vgxk4L0khIlSrBlyxaNZZaWlhw5coQLFy4o83klJCRw6dIlqlSpQtWqVSlVqhSQ9qkyNjaWTz/9lJEjR7JhwwZu3LjByZMnKV++vLLPF6MpIiIiXquNEj+RORmy0+5V/ZOd2Il169YRGBjIvn37qFSpkrKej48PGzdu1LjS/+OPP/D392fDhg3Uq1fvHZ/NuydTB2XtQ8VPSEHKJpVKxfDhw/n8888BePToEYUKFeLkyZOZRlmcPXuWoUOH0qtXL1q1aoW+vr5G9MSL0RQynaDIDVatWsXixYsJCwvDwsJCWR4bG8vz588zFKNBgwaxc+dOPv3005xorsiFpCBlk4ODA+vXr6d58+YkJSXRvXt3JkyYkOX6f//9N/b29nTr1o2YmBjCwsKUYva2JH4icxI/od2r+kdb7IRKpWLgwIGUL19emfqqadOmTJgwgcuXL1OhQgWN9QcPHkxSUhLe3t5A2ijD4sWL3/4kxEdNClI2de3alX///RcPDw9SUlLw9PSkQYMGhIeHZ7p+27Zt8fX1xdU17cmlV0VfvA6Jn8icxE9o9yb982LsxKNHjzJdp379+mzevFnzWKdOvVkjRZ4m8RO5iMRPaCf3ALST/tFO+idrH+q9R2ZqEEIIoROkIAkhhNAJUpCEEELoBClIQgghdIIUJCGEEDpBCpIQQgid8NEXpIiICNzc3DT+1KhRg88++4ygoKBs7+fMmTOMGTMGgDFjxnDmzJn31WQhhMiT8tz3kJYvX86mTZto3Lgx+fLlY8CAATndpGxL/y5AjcpVZEaCTMhMDdpl1T9vkoNUsmRJAO7fv0/Dhg05c+aMxozeFy9epEGDBty9ezfXzPQt30PK2of6HlKemqkhIiKChQsXsmHDBrZs2cLp06fp2rUrd+/exdPTkwEDBmiNmZg3bx4rV67Ey8sLX19f6taty/jx47ly5QoPHjzA0tKSWbNm8eDBA3x9falatSoXLlygaNGizJkzBzMzM7Zv387cuXMpWLAgNWrUQKVSMXXq1Nc6D8lDypxMrqpdVv3zpjlIu3btws/Pj7t372psHxcXx9ChQ+XL2+K1ffRDdukePnzId999x6RJk5RZtx8+fMiKFSsIDg5m2bJlPH36VCNmYuPGjezbty/L2bhPnDiBkZER69atY8+ePTx58oQDBw4AaZ8Qv/zyS7Zt24apqSmhoaE8evSIgIAAfv31VzZu3EhsbOyHOXkhXkN6DlK6tWvXUqdOHUAz20hfX5+9e/dqTLSqVqvp168fAQEB8uFAvLY8cYWUmprKsGHDaNeuHZ999pmyvHHjxhgbG2NhYYG5uTmxsbFaYyZeVr9+fczMzFi9ejXXr18nMjJSyZspWrQoNWvWBNIiJmJjY4mIiMDW1lYZ7nB3d2fv3r2vfT6Sh5Q1yUPSLrP+edMcJAsLCyIjI0lKSuKff/4hX758LF68mJo1a5KSkqKxPLeQPKSclScK0rx580hKSmLo0KEayw0N/3f66TEQ2mImXrZv3z7mzp1Lz5498fT0JCYmRomSyCySQl9fn9TU1Lc+H8lDypwM2WmXVf+8TQ5S+vZ2dnbkz5+f/fv3U7ZsWfbv38+jR4/w8/NTUmR1ndxDytqHykP66IfsDh8+zIYNG5g9e7ZGAcpKesxEcnIy8fHxdO/ePdNiBHDkyBHatGlDhw4dMDU1JTw8HJVKleW+7ezsOHPmDPfu3UOtVrN9+3b09PTe+NyE+BBWrVrFvHnzCAsLy1CMXnb16lXCwsIICwujVKlS7N69+wO1UnwMPvorpMWLF6NSqejbt6/G8gcPHtC1a9cM679OzESnTp0YNmwYv//+O0ZGRtjZ2WmNmLCwsMDf35/evXtjbGxM2bJlMTU1fe1zkjykzMlTdtppe8ouK9pykIR41/LcY99vau/evWzYsOGtQsZiYmJYuXIlvr6+6OvrM2nSJD799FO8vLyytb3ET2gnQy7aSf9oJ/2TNXnsW4ds376dyZMnM3r06Lfaj5mZGXFxcbi4uGBgYICVlRWdO3d+R60UQojcTQpSNrRt25a2bdu+9X709PTw9/d/By0SQoiPz0f/UIMQQojcQQqSEEIInSAFSQghhE6QgiSEEEInSEESQgihE+QpuxdERUXRs2dP9u/fr7Hc0tKSS5cu5VCrMlIlPiNF9fZTEH1salSuQkpCYk43Q2fVqFwF1bPnWqMmrl69Sq9evdDT08Pa2pr58+ej//9fnL169Sru7u7KFDI3b97Ey8sLtVqNhYUFa9askambxFuRgpQLSfxE5mQuO+0SEhKo6t1FY9nLURPpM+I3a9aMb775hi1btuDh4cHKlSuZM2cODx48ULadPXs2Xbp0wcfHhzFjxrBs2bJclS8mdI8M2WVTSEgIfn5+ys9eXl6Eh4cTHh5O79698fHxoVWrVgwcOJCkpCQg7T9s586dadWqFV5eXsp/ZicnJ3744Qfc3d3p0KEDt27dypFzEuLlqInjx4/TtGlTANq0aaPMRm9ubq5Eq6SrU6cOMTExQFoGkpGRTPgr3o5cIb3k3r17uLm5vdY2J06cYMeOHZQoUYLOnTtz6NAhKleuzPXr11m7di36+vqMGDGCrVu30rt3b+7fv4+joyNjx45l6tSprF69WqPYvYrET2RN4ie0e1XURHpkBMCdO3e4ceMGx48fp3Tp0ly8eJGUlBQloiEhIYHZs2fz888/k5SUhLu7e66Pb8jt7c/tpCC9pESJEmzZskVjmaWlpdZtqlatSqlSpYC0T5yxsbF8+umnjBw5kg0bNnDjxg1OnjypBANCWhZT+rZZBQBmReInMidDdtolJCS8MmoiX758yutRUVFUqlRJY31DQ0Pl5759+7J69WpatWrF77//zqxZs/j9998/3Am9YzKXXdYkfkLHpGcapUtO/t8VSmbZR2fPnqVPnz6kpqbSqlUrWrZsqbF9+jYv71eInGRra0tYWBgAO3bsUD44Zcbc3JwiRYoAUKZMGWX4Tog3JVdI2WRubs61a9dQq9VERUW98qm7v//+G3t7e7p160ZMTAxhYWFK6N/bkviJzEn8hHZJSUlaoyYAZs6cSd++fUlKSqJGjRp07Ngxy3WDgoLw9fVFpVKhVquZP3/+u26yyGOkIGVTw4YNCQ4OpnXr1lSsWPGVl/Zt27bF19cXV1dXAKytrbVmJb0OgwL5MZT4iQxOXTgvQy5aZNU/FSpU4OjRowBUq1Ytw8MLL4qOjlb+XrNmzQxfkRDibUgeUi4ieUjayT0A7aR/tJP+ydqHeu+Re0hCCCF0ghQkIYQQOkEKkhBCCJ0gBUkIIYROkIIkhBBCJ0hBEkIIoROkIGXD5cuXsbS0ZNeuXa9cN33S1ez67bff+O23396meUK8tufPn9O9e3ccHBz4/PPPuXLlCrt378bW1hYnJycmTZoEQGpqKt988w2Ojo40a9aMq1ev5nDLxcdMvhibDelfiF23bh2tWrV6p/vu1q3ba2+jSk5CpfdOm/FRqGlZDVXS85xuhs6qUqmi8vclS5ZgYmLC0aNHuXTpEj4+Ply6dImwsDAqVarEF198waFDh7h37x7Pnj3jyJEjHD16lKFDh2aY61GId0UK0iskJycTGhrK6tWr6dq1Kzdv3qR8+fI4OzvTvn17Dh06RGJiItOmTcPa2hqAjRs3MnXqVOLi4hgzZgzOzs74+flhb2+Pp6cn8L/Qv6CgIIDXypGJPRuBIfJ95pfFxydQqJBMrpoVE+v6yt/Pnz9PmzZtgLTfxcOHD1O1alUqVaoEQKNGjZSC1Lp1awAcHBxeeyJgIV6HDNm9woEDByhTpgwVK1akZcuWrFu3TnnNzMyMjRs30rVrVxYvXqwsL1y4MJs2bcLf31/m9xI6qU6dOmzbtg21Ws3Ro0d5/vw5CQkJXLx4EZVKxfbt24mPjycuLk6ZQBXAwMCAlBQJhxTvh1whvUJwcDAuLi5A2vx0w4YNY9CgQYBmhMTu3buVbVq2bAlAlSpV3ssMyAmJzzBIVb3z/X4M4uMlDykrJvwv78fGxoawsDDq1auHjY0N1atXZ/jw4fTo0QNTU1PKli1LYmIiiYmJnDp1ihIlSgBp955OnTqVg2fxfkkeUs6SgqTFw4cP+fPPPzl37hwrVqxArVYTFxfHnj17AM0IiRcZGBhkWP5izMSL0RVvomCB/DJklwkZsnu19Lnajhw5QocOHejQoQMREREkJCRw48YNDh48SMGCBfH09MTPz4+LFy8SGhqKn58fR48exc7O7qOd703mssvah8pDkoKkxZYtW3BwcGDp0qXKsqCgINauXfva+zIzM1OeUEqPhRYip1StWpWxY8cyY8YMzMzMWLZsGb///juNGjWiQIEC9OjRAysrK2rUqMGePXto2LAharWaX375JaebLj5iUpC02LRpE0OGDNFY1qNHD5YuXYqJiclr7atbt24MHjwYV1dXHBwcKF68+Bu3q4h1PfJJ7k8GJpKHpNXT+HgK/P/fixUrluGDUd++fenbt6/GMn19fRYtWvSBWijyOomfyEUkfkI7GXLRTvpHO+mfrEn8hBBCiDxFCpIQQgidIAVJCCGETpCCJIQQQidIQRJCCKETpCAJIYTQCVKQhBBC6AT5YuwLQkJCOHbsGAYGBnTt2pVatWq91+Pt27ePs2fPKnPjZZfET2RO4icyp6enh75R2heGnz9/zpdffsn169cxNTVl/vz5REdHM2zYMPT09Gjbti3ff/89AO3bt+fhw4cYGRlRoEABduzYkZOnIfIAKUiZmDx58gc5TosWLWjRosVrbyfxE5mTuewyZ2HXSPn7yzlIvr6+PHjwgI0bN1KxYkWaN2+Oq6srtra2XL16lXPnzmWYq1GI90WG7DKRnvqakpKCv78/Xbp0oUWLFvj4+PDs2TOioqJwd3dn+PDhuLi44O3tzePHjwHYvn07rVu3xtPTkzFjxuDn58edO3dwdHTk2rVrJCUl4erqSlhYGCEhIfj5+eXw2Yq85OUcpAsXLhAeHk7FihV5+vQpsbGxFC1alLt37/L48WNcXV1xcnJi27ZtOdxykRfIFZIWJ06cwMjIiHXr1pGamoq3tzcHDhzAysqKixcvEhAQQM2aNRkwYAChoaG0a9eOgIAAgoODKV68OAMHDsTExITSpUszbNgwxo8fj52dHba2tjRr1oyQkJA3apfET2RN4icyMklK4vyZtJmazc3NWb58OeXKlePs2bP8999//PPPP5w/f57Ro0dTsWJFbt26xePHj+nSpQtdu3YlLi6OPn36kC9fPiwsLHL4bN4viZ/IWVKQtKhfvz5mZmasXr2a69evExkZSUJC2hte0aJFqVmzJpA2c3JsbCwRERHY2tpSsmRJANzd3ZUJLDt06MCOHTsIDQ1960+bEj+RORmyy5yxsTF169bl+PHjTJgwgeHDhzNs2DAaNWpE3bp1sbe3x97enl69euHv78/u3bvx9/enWbNmFCpUCEhLi82fP/9HPdebzGWXtQ8VP5Hnh+wiIiK4e/cuAGq1WskygrSHDoYNG0b+/Pnx9PSkfv36SqbRixMMpmcd6evrk5qamulxnj9/TnR0NCqViujo6Pd4RkJk7e+//8bJyYmwsDA8PDyoWLEijRs3VoIkCxcujL6+Pnv37qVz584APH36lLNnz1KjRo2cbLrIA/L8FVJwcDDW1tb06NGDS5cuUa5cOW7evAmkhZi1adOGDh06cOvWLcLDw3F0dMxyX3Z2dkycOJF79+5RvHhxtm/frhSuwMBAHBwcqFevHqNGjWLNmjVv3GaJn8icxE9k7sWHEjLLQfr7779p06YN+fLlo3Tp0kq8yq5du3BwcEBfX5+AgACKFSuWg2ch8oI8X5D69evHiBEjWLVqFaVKlSIwMJDDhw8D0KlTJ4YNG8bvv/+OkZERdnZ2REVFZbkvCwsL/P396d27N8bGxpQtWxZTU1NOnjzJrl272Lp1KyYmJmzatImff/6ZokWLvlGbDYyMMTCW+ImXnT9zVoZcXiGzHCQ3Nzfc3NwyrBsYGPihmiUEIHlI71RMTAwrV67E19cXfX19Jk2axKeffoqXl9c72b/kIWkn9wC0k/7RTvonax/qvSfPXyG9S2ZmZsTFxeHi4oKBgQFWVlbKOLwQQgjtpCC9Q3p6evj7++d0M4QQIlfK80/ZCSGE0A1SkIQQQugEKUhCCCF0ghQkIYQQOuGjeKhh586d/PTTT6SkpKBWq3Fzc+Orr77C2dmZFStWULZs2Xd6vPe13+yS+InM5fX4iRdjJpYvX87y5csBePbsGSdPnuSHH36gc+fOlCtXDoAJEybQsGFDvL29iYyMxMDAgCVLllC9evWcOgWRx+X6gnT37l2mTZtGSEgI5ubmxMfH4+XlRcWKFXO6ae+NxE9kLq/PZfdizESvXr3o1asXAP3796d3796Eh4czffp0OnTooKy3ZcsWUlJS+Ouvv9izZw9jxowhODj4QzddCOAjKEgxMTEkJyfz7NkzAAoVKsTUqVOVL2/Nnz+fCxcukJiYyPTp07GxseHYsWPMnj2bZ8+eERcXx6hRo2jZsiV+fn6YmJhw7tw57t69S//+/enQoQOPHz9m+PDhREdHU7lyZZ4/T/sUnpqaSkBAAEeOHEFPT4/27dvTr18/wsPDWbx4Mfnz5+fatWtYWloyY8YMjI2NWbFiBatWraJw4cJUqlSJ8uXLM2DAgBzrP/Fxi4iI4Ny5c8yfP59ff/2V6OhoAgMDsbe3Z9q0aVSrVo2UlBRSU1OJi4vDyMgop5ss8rBcfw+pevXqtGjRgpYtW9KxY0d+/PFHUlNT+fTTTwGoUqUKmzdvxsvLi2XLlgGwatUqJk2axKZNm5g0aRJz5sxR9hcdHc2aNWtYuHAh06dPB2Du3LnUrFmT0NBQevTowYMHDwD47bffuHPnDlu3bmXDhg3s3r2bsLAwIC264vvvv2fHjh3cvn2bQ4cOcfHiRVavXk1ISAhr1qzh33///YA9JfKigIAAxo0bB4C9vT1BQUEcPHiQp0+fsmjRIkxMTIiMjKR69er07duXgQMH5nCLRV6W66+QIG0s3MfHh0OHDnHo0CE6d+7MjBkzAGjZsiWQVph27doFwI8//sgff/zBzp07OXXqFPHx8cq+GjVqhJ6eHtWqVVNC944dO8bMmTOBtEiK9DH48PBwPDw8MDAwoECBAri6unLkyBGcnZ2pWrUqpUqVAqBy5crExsby77//0rx5c0xMTABo164dcXFxr32+koeUtbych/Ri7hHAkydPOHnyJKamphw/fhw3NzdiYmKIiYmhZs2a7NmzhyNHjmBjY4Ovry/R0dF07dqVtWvX5tmpqSQPKWfl+oIUFhZGQkICbdu2pUOHDnTo0IH169ezceNGACVO4sUZj7t3706DBg1o0KABjo6ODBs2THkt/T/ii+unx0ukS9/ny1ETarUalUqlsZ8Xt9cWT/E6JA8pc3n9HlJ67lG6rVu34uLiQt26dVGr1ZQuXZqIiAjKli3LmjVraNWqFQ8fPsTIyIi6desSHx+Pvr4+NjY2Sg5SXiJz2WVN8pCyKX/+/MycOVOZhVutVnPhwoUss1seP35MZGQkgwYNokmTJuzbt08pIllxdHRky5YtAJw+fVqJp3BwcGDz5s2oVCoSExMJDQ2lQYMGWvdz4MABnj59SlJSErt379YofEK8S5cuXaJSpUpA2oeisWPH4unpSdOmTUlISKBv374MGTKEf/75h8aNG+Ps7ExAQECeLEZCN+T6KyQHBwd8fX355ptvSE5OBqBx48b079+f0NDQDOubmZnRsWNH2rVrh6GhIQ4ODjx79kxJgs3MwIED8fPzo127dlSqVEkZsuvSpQuRkZG4ubmRnJyMq6srn332GeHh4Znup1q1avTs2ZMuXbpQsGBBzM3N32hoRPKQMpfX85Be/nAzfPhwjZ8dHBzo37+/xjIjIyPWr1//3tsmRHZI/MQHdOPGDQ4cOKA8jvvtt9/SqVMnnJ2ds7W9xE9oJ0Mu2kn/aCf9kzWJn/gIffLJJ5w5cwYXFxf09PRwcnKiefPmOd0sIYTQCVKQPiBjY2PlaT0hhBCacv1DDUIIIT4OUpCEEELoBClIQgghdIIUJCGEEDpBCpIQQgidkOefsgsJCeHYsWMYGBjQtWtXatWqldNNeiXJQ8pcXslDejH3CGDKlCls3bqVpKQkfHx8cHR0pF+/fqjVamxsbAgKClKmu7p//z4NGzbkzJkz5M+fP6dOQYhM5fmClG7y5Mk53YRskzykzOWVuexezD0KCwvjr7/+4vDhwyQkJDBjxgxCQ0MJCAigSZMm9OrVi61bt+Lh4cGRI0f46quvuHv3bg62XoisSUH6f15eXvj6+lK3bl3Gjx/PlStXePDgAZaWlsyaNYsHDx7g6+tL1apVuXDhAkWLFmXOnDmYmZmxfft25s6dS8GCBalRowYqlYqpU6cybdo0Dh8+jL6+Pi1btsTX15egoCAAJQMpp9NnRe62a9cuatWqhYeHB3Fxcfz444+MHTsWAwMDkpKSiI6OpmTJkkDaldXevXtlNgKhs6QgveTEiRMYGRmxbt06UlNT8fb25sCBA1hZWXHx4kUCAgKoWbMmAwYMIDQ0lHbt2hEQEEBwcDDFixdn4MCBmJiY8N9//3Hw4EF+//13EhMTGTVqlBLs97YkfiJreSF+4sWYiYsXL3Lnzh0CAwP577//6NChA8HBwURHR+Pj44OJiQmJiYkcP34cBwcHIiMjSUpK4p9//pHppzIh8RM5SwrSS+rXr4+ZmRmrV6/m+vXrREZGKhOvFi1alJo1awJQtWpVYmNjiYiIwNbWVvkU6u7uzt69eylZsiT58uWja9euNG/enGHDhr2zNwCJn8hcXhmyezFmwtLSEicnJxwcHACYOHEi5cuXp169eri4uLB06VJWrFjBr7/+qszVZmxsjJ2dndxDeonMZZc1iZ94jyIiIpRxdLVardzwBdi3bx/Dhg0jf/78eHp6Ur9+fSUL6XUyjgwNDdmwYQODBg3i8ePHdO3alRs3bmTIVkqfoVyIN+Hk5MTOnTtRq9Xcvn2b+Ph4+vTpw5UrVwAoXLgw+vp58r+5yIXy5BVScHAw1tbW9OjRg0uXLlGuXDkl4+jIkSO0adOGDh06cOvWLcLDw3F0dMxyX3Z2dkycOJF79+5RvHhxtm/fTr58+Th//jw//PADK1euxNHRkfPnz3Pjxg3Mzc2VeIrTp09z//79126/xE9kLq/ET7wYM+Hi4sLBgwext7cnNTWV+fPnU7hwYXr16oWxsTEFCxZk6dKlOdhaIbIvTxakfv36MWLECFatWkWpUqUIDAzk8OHDAHTq1Ilhw4bx+++/Y2RkhJ2dnRL+lxkLCwv8/f3p3bs3xsbGlC1bFlNTU2rWrEmdOnVwcXGhQIEC2NnZ0aRJE548ecKuXbto27YtVlZWyhDg6zAwMsbAWMb/X3b+zNk8OeQyffr0DMvSf58zExkZ+R5bI8SbkzyktxQTE8PKlSvx9fVFX1+fSZMm8emnn+Ll5fXOjyV5SNrJPQDtpH+0k/7JmuQh5RJmZmbExcXh4uKCgYEBVlZWdO7cOaebJYQQuY4UpLekp6eHv79/TjdDCCFyPXn8RgghhE6QgiSEEEInSEESQgihE6QgCSGE0Am59qGGp0+fMnPmTP7++28MDAwwNTXFz8+Pp0+fMm/ePFauXPnB2zRnzhysra1p0aLFez2OxE9k7mOOn3g5csLW1pYiRYoAULFiRW7cuKG8dvHiRXr16sXUqVM1oinatm0rjzULnZYrC1Jqaip9+/alQYMGbN68GUNDQ44ePUrfvn0ZN25cjrVr0KBBH+Q4Ej+RuY95LrsXIyeePXsGpEVPvOz69et07twZf3//DNEU33333YdqrhBvJFcWpPDwcO7cucPAgQOVebocHByYMmUK8fHxPHr0iL59+3Lz5k0qVqzI3LlzMTY2Jjg4mF9++QU9PT2srKwYO3YshQoVwsnJiVatWnH8+HEMDAwIDAykXLlyhIeHM2nSJAwMDKhTpw7Xrl1j5cqVnD17lrFjxwLQuHFjtm3bxv79+/Hz88Pe3h57e/vXjqoQIrtOnTpFQkICn3/+OSkpKQQEBCiTqw4ePGhHyzIAACAASURBVJhp06ZhYmKSIZqid+/eOdxyIbTLlQXp/PnzVK9ePcOkkU2bNiU8PJzbt2+zaNEiPvnkEzp37sxff/1F6dKlWbRoEevXr8fc3JwJEyYwb948Ro4cyf3793F0dGTs2LFMnTqV1atXM3ToUEaMGMHixYupXr06kyZNUo4zYsQIRo0aRePGjZk3b16mbXydqIrXJfETWftY4ydejJyIjIykU6dOuLu7c/PmTTp27EhwcDA3btzgv//+w8zMjOPHj2eIpvjuu++oUaOGxlx4QpPET+SsXFmQ9PX1tU5fUb16dcqVKwdA5cqViYmJISoqiubNm2Nubg5Aly5dGDVqlLJN48aNgbRYiYiICC5fvkzRokWpXr06AB07dmTy5Mk8evSIBw8eKOt36tSJkJCQDG14naiK1yXxE5n7mIfsXoycsLa2pn379hQoUIB69eoxdepUypQpQ3BwMN99912W0RSjRo2ifPnylChRIsfOQ5fJ1EFZk/gJLaytrTl//jwvT8M3a9Ys1Go1hob/q7PpcQ8vR0So1WpSUlKUn9MLXPr6BgYGmcZKvFwIjYyMMm3j60RVCPE6fv75Z4YOHQrA7du3iYuLo3Tp0uzbt4/WrVsr670cTZGYmEjRokVzqtlCvFKuLEj16tWjaNGizJs3D5Uqbejqzz//JCQkhEePHmW6jb29Pfv37+fx48cArF+/ngYNGmR5jEqVKhEXF8elS5cACA0NBaBQoUJUqlSJffv2aSzPDjs7O86cOcO9e/dQq9Vs375dhk/Ea+vTpw+PHz/GycmJLl268PPPP2NoaEh0dLRGwXFxccHW1hZ7e3tcXV0ZOXKkRvaXELomVw7Z6enpsWDBAqZMmYKLiwuGhoaYm5vz008/8eTJk0y3qV69Ol9//TVeXl4kJydjZWXFhAkTsjyGsbEx06dPZ+TIkfwfe/cdV2X9/nH8xUZFA/dAjVDRxFwp4GJICcgQMUUN9OvKnVsUcoQLw3LmLnPlpNwjUyxQsRxpSaKZ5gjMXAxZh/P7gx8nxuEIyjjI9Xw8fDzk9j73uc6tcnF/zn2ut66uLhYWFqqEzZCQEIKCgli2bBmWlpYFrju/qIrCkjwk9V7lPKTsP7gYGhqydevWPPvcvXs3z7bs0RTy/ojQekqhlkKhUIaEhCgTExOVSqVS+cUXXyjnz5+fZ7/bt28rHR0dC3TMhw8fKpcsWaJUKBRKpVKpDA4OVm7cuLHANSUnJyt//vlnZXJycoEfU578/PPPpV2CVpPzo5mcn/yV1PeeMnmFVBJ0dXUxNTWlV69eGBgYUK9ePebOnftSx5SoCiGEyJ80JA2GDRvGsGHDNO5jbm7O8ePHC3Q8iaoQQoj8lcmbGoQQQrx6pCEJIYTQCtKQhBBCaAVpSEIIIbRCuWtIhw8fpmfPnnh6euLh4cG6desAGDp0KHFxcfk+zsnJiTt37pRUmUIIUe6Uq7vs4uLiCAkJISwsDDMzMxITE/Hz88PCwoK1a9eWdnkFlpGRTkZGuftZ4rmav9mUjIy00i6jSOmgg47uf/9Nc+cgDRo0iEmTJqGjo4ObmxszZswAMqNQIiMjMTExISQkRONUEiG0RblqSI8ePSItLU2VJ1OpUiUWLFiAkZERTk5ObNy4kRo1ajB79mzOnTuHgYEBI0eOxM3NDYAVK1YQHR3Ns2fPWLhwIS1btsTPz4/Ro0djY2PDnTt38Pf35/jx48TExBAcHExSUhIPHz5k2LBh9O3bl2XLlhEXF8etW7e4e/cu7733HiNGjCjU60iOv4EiWUYO5ZaUmEjFSpVKu4wiVfE1K7L+ptXlILVt25Zdu3ZhYWGBo6MjHh4e3L17l6tXr3L27FkePnyIi4sLP//8c8kXL0Qhlasfs5s2bUrXrl1xdnamV69efPLJJ2RkZNCwYUPVPps2bSIpKYlDhw7x5ZdfsmLFClJTUwFo1KgR3377LX5+fqxfv17jc+3cuZORI0eye/duNm7cmGOEy9WrV1m/fj07d+5kzZo1PH36tHhesHilZM9BcnJy4syZM0RFRWFhYUFCQgJPnjyhWrVqXLlyhW7duqGrq0v16tXR09MjNja2tMsX4rnK1RUSwOzZsxk5ciQRERFERETQu3dvQkNDVX/+008/0bt3b3R1dalRowYHDhxQ/ZmzszOQ2ZiOHDmi8XkCAgL48ccfWb16NTExMSQl/ZfTY2Njg6GhIdWqVcPU1JT4+PhCzbR79iyJtNQC716uJCUmlnYJRUrfOJXfrlwC8s9Bio6OZvr06VhYWHD79m0qVarE5s2b6dChA7GxsVy+fJmoqCjMzc1lnt1zyPkpXeWqIYWHh5OUlISbmxs+Pj74+PiwY8cOdu3apdpHX18/xyDLW7duUadOHQDVpOTcE7qV/x+DkT3OYty4cVSpUgVHR0fc3NzYv3+/6s/URVMURoUKFTEwkCW73F7FJTtDo+fnINnY2DBw4ECCgoI4evQos2fP5vHjx0yaNImWLVvSrl077O3t+eOPPyTvRwPJQ8qf5CEVA2NjYxYtWqS6W06pVBIdHU2zZs1U+7Rr146DBw+iVCr5999/ef/991VLduqYmZlx/fp1gBxhe5GRkYwdOxZnZ2d++OEHAFVUhhAvIncO0pMnT+jduzePHj0CoHLlyujq6hITE0PNmjX58ccfVdPqTU1NS7N0IQqkXF0h2draMnr0aIYPH05aWubdWJ07d2bUqFGqXKN+/foxZ84cPD09Afjoo480xowPGTKEgIAAdu/eTdeuXVXbx4wZQ79+/TAyMqJp06bUq1evyG4bN678BkZGr2bMwsvQN07F8BU7Lzr8dyU8ePBgBg4cSKdOndDR0eHLL7/kn3/+wdXVFSMjI+rUqcO6devQ19fn8OHDrF+/HmNjY1asWFGKr0CIgtNRFna9SJSarMtma2trjRHu5ZUsuWgm50czOT/5K6nvPeVqyU4IIYT2koYkhBBCK0hDEkIIoRWkIQkhhNAK0pCEEEJoBWlIQgghtII0JCGEEFpBaxvSnTt3cHJyyrPdysoq38dcvnyZwMBAAPz8/IiKiirSmrIyk77//nuWLFlSpMcujMz4iTT5letXVvxEWf6lzEjP8/d9//596tevz++//87FixextbWlU6dODBo0iIyMDNV+//zzD40bN1ZNBReirHmlJjW0aNGCFi1aFNvxszKTatWqlWMqQ0mT+An1XoVZdtnjJgDS0tL44IMPqFChApA5HHjGjBm4ubnRv39/Dhw4gIeHB0eOHCEgIEBjyKQQ2k5rr5A0USgUzJ8/H29vbzw9PdmwYQMAUVFR+Pn55dl/1apVuLm54eHhwYIFC1AoFNy5c4cePXowefJk3N3dGTBgAI8fPwbg4MGDuLi40LNnTwIDAwkICAD+S40NCwtTbTt06BC9e/fG09MTFxcXzp8/D2ReoS1cuJA+ffrwzjvvcPLkSQBiY2N5//338fDwYOLEiXTp0qW4T5cowyZNmsTw4cOpW7cukBnQ9/DhQ5RKJfHx8RgYGACgq6vLsWPHqFq1ammWK8RL0eorpPv37+Pl5ZVn+44dOwD45ptvSE1NZfDgwVhbW6s9xsmTJzl+/Di7d+/GwMCAMWPGsG3bNuzt7fn999+ZN28eb775JmPGjGHfvn10796defPmsXv3bmrUqMHYsWPznWWXkZHBtm3bWLVqFVWrVmXXrl2sWbOGVatWAZk/3W7fvp3jx4+zZMkS7O3tmTt3Lq6urvTv35/vvvsuxxTwgpL4ifyV9fiJ7HET+/btIzU1lerVqxMfH89vv/2Gnp4eo0aNIigoCBMTE6pUqcK5c+eoWrUqN2/eJDU1lfPnz+c73kXiFTST81O6tLoh1axZkz179uTYZmVlxenTp4mOjubMmTMAJCUlcfXqVRo1apTnGGfOnKF79+6qJQ8fHx++/fZb7O3tqVatGm+++SYAjRs35smTJ/z888+0bt2aWrVqAdCjR48cU7yz09XVZcWKFRw/fpw///yTs2fPoqv730Vn586dVcfOuvqKjIxk/vz5ALzzzjuFykHKIvET6r0KS3bZ4ybGjx+Pjo4OEydO5I8//iAkJISLFy9y4cIFmjdvzooVK9iyZUuO4amGhoa0adMGY2PjPMeWWW2ayfnJX0nFT2h1Q8qPQqFg8uTJvPvuuwA8fPiQSpUqcfHixTz7Zn/TN0tWbpG6XCJdXV21j1EnMTGRXr164enpSbt27bCysmLLli2qP886fvb8JD09vULnH4nyKSu2BMDBwYFVq1bRo0cP1Q8xdevWJTIysrTKE6LIlcmGZGtry44dO3B0dCQ1NZV+/foxe/bsfPdduXIlffr0QV9fn927d2Nra5vvsdu0acPHH3/M/fv3qVGjBgcPHsx3+ePmzZvo6OgwfPhwlEolU6ZMeW7mkZ2dHfv27aNfv36cPHnyheLLJX5CvVchfkIHzVe+69atw9fXF319fQwNDVU32gjxKiiTDcnX15dbt27h7e1Neno6PXv2xMbGRu1t3o6OjkRHR+Pj40N6ejqdOnXi/fffJzY2Vu2xq1atSlBQEIMGDcLQ0BBzc/N8l9WaNm1Ks2bNcHV1RUdHh06dOj13DTowMJCpU6eyY8cOmjZt+kJLdrq6+ujqGhT6ca+6365cemWXXMLDw1W/13RVdPPmzeIvRojiohQ5PHz4ULlkyRKlQqFQKpVKZXBwsHLjxo1KhUKhbN++vfLff/99qeN/9dVXymvXrimVSqXy119/VXp7exf4scnJycqff/5ZmZyc/FI1vKp+/vnn0i5Bq8n50UzOT/5K6ntPmbxCKk6mpqY8ffoUd3d39PT0aN68OT169MDJyYl27dq99G21DRs2ZMKECejq6mJkZERwcHARVS6EEGWbNKRcdHR0CAoKyrM9+5LJy7C3t8fe3r5IjiWEEK+SMvnBWCGEEK8eaUhCCCG0gjQkIYQQWkEakhBCCK0gDen/RUVF0bp1a7y8vPD09MTV1ZWvvvpK42MCAwO5fPlyjtiLrG1CvKjscRNZxo8fr5qRCDB27Fjatm2Lg4MDDg4OPHnypDRKFaJIyV122VhbW7Np0yYAEhIS6N69Ox07dlQ7Iw9g7ty5qt9nxV5k31ZcMvOQ5GeJ3LLykMoSHXTQ0f3vv2HuuIl//vkHf39/YmJimDx5smq/8+fPc+TIEapXr17iNQtRXKQh5SMlJQU9PT0qV67MpUuXmD9/PsnJyZiZmTF79mzq16+Pn58fo0ePBmD58uVs2rQpx7bVq1djbGzMH3/8gZWVFaGhoRgaGrJx40Y2b95M5cqVeeONN2jQoAFjxowpcG2Sh6ReWRyumjv/KCtuImsAb0JCArNmzeLQoUOqfTIyMrh27RrDhg0jLi6OwYMHM2jQoBKuXIiiJw0pm19//RUvLy8yMjL466+/cHV1xczMjKFDh7Jq1Srq1q3Ljz/+yEcffaTKYNLkwoULHDp0iJo1a9K7d28iIiKoW7cuW7ZsISwsDAMDA/z8/GjQoEHxvzih9TZs2ECNGjXo1q2bqiFZWFhgYWGRoyElJiYyZswYJkyYgEKhwNHRkbfffpu33nqrtEoXokhIQ8om95LdkCFDWLt2Lbdv32bEiBGq/RISEgp0vMaNG1O7dm0ALC0tefLkCbdu3cLR0VGVsdS9e/dCD1iVPKT8lbU8pOz5R0uXLkVHR4dvvvmGmJgYfHx8+PTTT6levTr37t0jJSWFc+fOoVAo6NKlC9HR0QC8+eabfPvtt6SlPX+5UvJ+NJPzU7qkIeXDxMQEV1dXjh07hrm5uSqXSaFQ8ODBgwId42XjLfIjeUjqlcUlu+z5R1lpw/Bf3ETTpk2BzKiJ2rVr07ZtW6Kjoxk6dCjnz58nIyOD69evM3XqVJo3b67xuSTvRzM5P/krqTwkeWc8HwqFgrNnz9KqVStVcB/A7t27mTRp0gsf187OjpMnT5KQkEBqaipHjx7NkZckxPM0a9aM/v37Y2tri729Pf7+/s9tRkKUBXKFlE3We0g6Ojqkp6djZWXFiBEjcHJyYu7cuaSkpGBiYkJISMgLP0eTJk3w9/enT58+VKxYETMzs3zzlvIjeUjqlcU8pPzyj3LPTpw1a1aOr6dMmcKUKVOKqSohSoc0pP9nY2PDhQsX1P5Z69at2bVrV57tWe83HTt2jIoVK+bYlnXMLAsWLADgzz//JC0tjQMHDgAwYsQILC0tC1Wr5CGp9yrnIQlRHkhDekkHDx5k7ty5TJ8+vUD716tXj8uXL+Pu7q4K9XN0dCzmKoUQQvtJQ3pJbm5uuLm5FXh/Q0NDFi1aVIwVCSFE2SQ3NQghhNAK0pCEEEJoBWlIQgghtII0JCGEEFpBGpIQQgit8Eo2pMOHD9OzZ088PT3x8PBg3bp1ADg5OXHnzp1ie96wsDACAgIKvH9cXBxDhw4t9PNkxk+kya9cv7LiJ7TtlzIjPcffn0KhYNCgQXTs2JEuXbrwxx9/cOXKFTp16kTHjh0ZOXIkCoUCgNDQUNq2bUu7du345ptvCv1vRYiy5JW77TsuLo6QkBDCwsIwMzMjMTERPz8/LCwsSru0PGrVqsXatWsL/TiJn1BPW2fZ5Y6Y2LdvHwCRkZGEh4czYcIEdHR0mDdvHl26dGHgwIHs3bsXR0dHli5dyvXr10lMTKRVq1Z4e3uXzosQogS8cg3p0aNHpKWlkZycDEClSpVYsGCBajzPihUriI6O5tmzZyxcuJCWLVty9uxZPvvsM5KTk3n69CnTpk3D2dmZgIAATExM+O2334iLi2PUqFH4+PgQHx/PlClT+Ouvv6hfvz6xsbEsX74cgFu3buHn58e9e/ews7Njzpw5pKenM2vWLK5du8aDBw+wsrLi008/5cGDB/j7+3P8+PFSO1+i5PXo0QN3d3cg899LrVq1WLlyJXp6eqSmphIbG0utWrWoVKkSDRs2JDExkcTERHR1X8kFDSFUCtWQfv/9dzZv3sytW7cIDQ3lu+++o379+tjb2xdXfYXWtGlTunbtirOzM82aNcPGxgYPDw8aNmwIQKNGjZg/fz6bN29m/fr1LF26lM2bNzNnzhwsLS05ffo08+bNw9nZGYDY2Fi2bt1KTEwM/v7++Pj4sGLFCiwsLFi5ciWXL1+mT58+quf/+++/+fbbb6lYsSLOzs5cu3aNx48fY2BgwPbt28nIyGDAgAGcPHnyhQdiSvxE/rQxfiJ7xER2M2fOJDw8nJCQEC5evMjff//NyJEjMTEx4dmzZ5w/f55KlSrRuHFjMjIyGDhw4EvHI0i8gmZyfkpXgRvSjz/+yJgxY3B1deWXX34hNTWVhw8fsmDBAubPn4+Hh0dx1lkos2fPZuTIkURERBAREUHv3r0JDQ0FUDWaRo0aceTIEQA++eQTTpw4weHDh/nll19IzPZNrWPHjujo6NCkSRMeP34MZC61ZB2vRYsWNGnSRLX/22+/jampKQANGjTg0aNHtG/fHlNTU7Zs2cKNGze4efMmSUlJL/z6JH5CPW1dssseMZHd/v37iY2NxcbGhitXrtC2bVvc3d1Zt24dGzduxMfHh5SUFNX7nt26dcPX15f27du/UB0Sr6CZnJ/8aV38xGeffca0adOYP38+enp6AIwdO5bAwEA+//zzYiuwsMLDwzl48CC1atXCx8eHzz77jKCgINVw1Kzas0c+9OvXj0uXLmFtbc3w4cNzHC9rqS/7/np6eiiVSrXPr6//X4/PykD6/vvvmTRpEsbGxvTs2ZN27drl+3jx6tu0aZMqEbZixYro6uri7e3NtWvXAKhcuTK6urqYmZlRoUIFjIyMMDY2xtTUVPVDkRCvogJfId24cYMOHTrk2d6xY0fVfy5tYGxsTHBwMG+99Rbm5uYolUqio6Np1qwZ169fz7P/48ePuXnzJlu3bsXQ0JDQ0FDVHU75sbOzY9++fTRt2pSrV69y7do1jZlGp0+fxtXVFR8fH27fvk1UVBR2dnYv/holfkItbY2fyB0x0bNnT/73v//RpUsX0tLSWLx4MTVq1GDgwIEYGhpSsWJF1q1bR506dTh27Bi2trbo6urSqVMn3nnnnVJ6FUIUvwI3JHNzcy5evEj9+vVzbD9+/HiebaXJ1taW0aNHM3z4cFWkc+fOnRk1apTq7qbsTE1N6dWrF927d0dfXx9bW1uSk5M1LqmNGjWKadOm4eHhQYMGDahevTrGxsb57v/ee+8xadIkDhw4gIGBAW3atHmp288lfkK9shI/UalSJXbs2JFne2RkZJ5ts2fPZvbs2SVRlhClTkdZwLWjY8eOMWXKFHr16sW2bdsYNGgQt2/f5siRI3zyySe4uroWd61aY8+ePZibm9O2bVvu3bvH+++/z7Fjx4r9LqisdVxra+tCh/qVB/IegGZyfjST85O/kvreU+ArJGdnZ7Zu3coXX3xB48aNCQ8Px8LCgi1bttCyZctiK1AbvfHGG8ycOZOMjAx0dXX5+OOP5ZZcIYR4SYW67btBgwZMmDCB2rVrAxAREVHotNNXQYsWLQgLCyvtMoQQ4pVS4B/rL168iKOjI5s3b1Ztmz9/Pi4uLkRHRxdLcUIIIcqPAjekefPm8d577zFx4kTVtgMHDuDl5UVwcHCxFCeEEKL8KHBDiomJoU+fPnlub+7Tpw9Xrlwp8sKEEEKULwVuSObm5mpvS42KiqJGjRpFWpQQQojyp8ANacSIEcyZM4cpU6bw1Vdf8dVXXxEQEEBwcDCjRo0qzhpLxZ07d3Bycsqz3crKKt/HREVF4efnV6jnGTp0KHFxcYWuT5Q96mInsowfP55Vq1apvpbYCVEeFfguu+7du1O1alW2bdvGzp07MTAwoGHDhmzYsIE2bdoUZ42vtBeJn8jMQ5LbzHPLykPSFjrooKP7338xdbET69atw9/fn5iYGCZPngxkTg+R2AlRHhXqtm87O7uXGnnzqlAoFCxcuJCzZ8+iUCjo2bMnAwcOBDLjLwYPHsz9+/d56623mDlzJoaGhvzwww8sXbqU9PR0zM3NCQ4OxszMDCcnJzZu3Ii5uXmBn1/ykNTTtuGquXOQ1MVOJCQkMGvWLA4dOqTaT2InRHlV4IaUmppKWFgYly9fJj09Pc9w0IULFxZ5caXt/v37eHl55dmeNfblm2++ITU1lcGDB2NtbQ1kLvUtX76chg0bMn78eL7++ms8PDxYtGgRGzdu5LXXXmPbtm2EhoYyd+7cEn09ovTp6+szYMAAvvnmG3bt2oWFhQUWFhY5GhJA/fr1efPNN1EoFEybNq2UqhWiZBW4IQUFBXH06FE6d+6MiYlJcdakNWrWrMmePXtybLOysuL06dNER0dz5swZAJKSkrh69SqNGjXi7bff5vXXXwfAw8ODsLAwGjRowN9//42/vz8AGRkZvPbaay9cl+Qh5U+b8pDyy0EaO3Ys/fr1Y8CAAezcuZMKFSpw7949UlJSOHfuHCdPniQmJobdu3cDMGbMGKpWrar6oedlSN6PZnJ+SleBG9LJkyf59NNP1b7RX94oFAomT57Mu+++C8DDhw+pVKkSFy9ezBE/oVQq0dfXR6FQ0KZNG9Wb1ikpKTkylwpL8pDU07Ylu9w5SJs2beLOnTtMmzaNp0+fYmxszNtvv42xsTF169aldu3atG3blqSkJI4dO4adnR06OjqYm5tTp06dl56zJrPaNJPzkz+ty0MyNjbWqqnepcnW1pYdO3aQlpZGYmIi/fr14+LFi0DmP+p79+6RkZHBt99+S4cOHWjZsiUXL17kzz//BODzzz9/JZc4hWY9e/bkwoULdOnShW7durF48WK1U+I7d+5Mu3btsLW1xc7OjiZNmkjshCgXCnyFNGrUKObNm0dgYCD169fHwCBn/EF5euPV19eXW7du4e3tTXp6Oj179sTGxoaoqCgaNWrE9OnT+eeff7C1taVXr17o6ekxb948xo0bR0ZGBrVq1eKTTz554eeXPCT1tC0PKXcOUn6xEwCzZs3K8bXETojyqMDxE/b29vz777/5htfJPLviJ/ETmsmSi2ZyfjST85M/rYufeJmf6IUQQojnKXBDat++fXHWIYQQopzT2JAcHBz45ptvMDMzw97ePs9g1ezCw8OLujYhhBDliMaG9OGHH1Lp/2+jHTduXIkUJIQQonzS2JCyz8969uwZLi4uVK1atdiLEkIIUf4U+F7tLVu20KVLFwYPHkxYWBjx8fHFWZcQQohypsAN6cCBA4SFhdGqVSvWr19Phw4dGDFiBPv37+fZs2fFWaMQQohyoFDTvps0aUKTJk0YM2YM169f5+DBg8yYMYOPPvqICxcuFFeNJe7OnTu4uLhgaWmZY/uqVauoU6dOnv2//vprAPr27YuXl1ee+XdFLTU9tRA/SpQfTZo2ISUtpbTLQFdHFwP9/z44npaWxqBBg7h58yYpKSkEBQVhbm7O8OHDMTIyolWrVixZsgRdXV02bNjAypUrUSgUeHl58dFHH5XiKxGiZBWqIQEkJCRw4sQJjh49SkREBPXq1aN79+7FUVupUjdYNT99+/ZV/b64mxHAhT9+QalToM8zlytJSUlUrFixtMvAtmnOj0hs3ryZatWqsWnTJv79919at25NzZo1Wbp0KR06dCAoKIitW7diZ2fHypUrCQ8Px8jIiJkzZ5KWlpZnKooQr6oCN6Rdu3Zx9OhRTp8+Ta1atejevTujR4/WmKD6qgkICKB9+/b07NkTyJz8ffXqVZYtWwZkTmXO2hYXF8f06dOJj4/n/v37eHt78+GHHxIWFsaPP/7IkydPuH37Nh07dswzNka8Wt577z169eql+lpfX587d+7QoUMHADp27MiePXtITEzk7bffZsCAAfz9998EBgZKMxLlSoEb0tKlS3FxcWH06NG89dZbxVmTVsidheTh4VGox+/fvx93d3e8vb2Jj4/H3t5eFW9+4cIFNAmKmgAAIABJREFU9u/fj56eHi4uLvTt27dQjf3Zs2dkkFGoesqLpKSk0i6B1NRUfr2UdzJyYmIiEyZMYPDgwezYsYM1a9bQtm1bvvjiC1UQ39GjR/niiy9ISUlh8ODBbNy4kcqVKxdZbRKvoJmcn9JVqPgJHR0dEhIS+O2331AoFDRs2PClcn20mbolu4CAgAI/fvDgwZw5c4b169dz7do10tLSVDd/tG7dWpUpVb9+fZ48eVKo2ipUqCBLdmpoy5KdoaFhnplot2/fxtvbm5EjRzJo0CB69erFhx9+yJ49e2jXrh1PnjzBysoKPT09unTpAmT+O6lYsWKRzVeTWW2ayfnJX0nFTxS4IaWlpRESEsL27dtJT0/PfLC+Pt27dyc4OBhDQ+2ZslxcdHR0VEm5aWlpGvddsGABt2/fxt3dHWdnZ06dOqV6bPbhhNmPKV5NcXFxvPvuuyxfvpyuXbsCmXetfvHFF9StW5cxY8bg6upK/fr1WbFiBcnJySgUCq5cuUKjRo1KuXohSk6BG1JISAg//PADK1eupHXr1mRkZHDhwgXmzp3LZ599xtSpU4uzTq1gamrK9evXATh27JjGfSMjI5k9ezZt2rQhPDycuLg4MjKKZpmttWXLcvEDQGGlpqZqxXnR1cl5C+S8efN49OgRwcHBBAcHAzBx4kTc3NyoWLEijo6OuLm5AZlX1h07dkSpVPLRRx/JB9FFuVLghnTgwAGWLl2aY8iqvb09xsbGTJgwoVw0pL59+zJu3Dg8PDywtbWlRo0a+e77wQcfMGXKFIyNjalduzbW1tbcuXOnSOow1DfEyEDiJ3L79dKvWrnksmTJEpYsWZJnu7r3JceNGydjukS5VeCGpFQqMTMzy7Pd1NRUK95ILkrm5uYcP348z/YGDRoQFham+jowMBCA+Ph4atWqBcDVq1cBcHd3x93dXe3xs+7Sg8xYayGEEIX4eKWtrS2hoaE5RgY9ffqUTz/9FBsbm2IpriyYP38+3333HQ4ODqVdihBClGkFvkKaPn06/v7+dOnShQYNGgDw119/8frrr7NixYpiK1DbTZs2jWnTppV2GUIIUeYVuCEZGRmxf/9+fvjhB27cuIGRkRGWlpZ06NBBY06SEEIIURAFbkheXl58/vnndO3aVXXrqhBCCFFUCvwekpGREampqcVZixBCiHKswFdInTt3ZtCgQXTp0oV69erl+HAnZKbLCiGEEC+qwA0pJiYGa2trHj58yMOHD3P8WVl5Dyk9PZ21a9eyd+9edHR0UCgUeHt788EHH5Taa1iyZAnW1taFWgaV+An1SiN+oqBREx4eHjRu3BiAESNG0KdPHyZPnkxERATp6ekMGzaMoUOHlmjtQmib5zakvXv3cvToUWrUqIGTk1O+n60pC2bPns2DBw/Yvn07VapUISEhgVGjRlG5cmX69+9fKjW9yJWlxE+oVxqz7AoSNTFjxgwmTJjAxIkTVfudOHGC69evc/r0aVJSUmjevDm9evVS+1k/IcoLjQ1pzZo1LFmyBDs7O9LT05k2bRoxMTFMmDChpOorMrGxsezdu5cffviBKlWqAGBiYsKMGTO4fv16vtESLxIjsWjRIo4cOYKZmZmqkb/22mssXLiQvXv3Ehsbi5+fHzt37uSzzz7L8byibFMXNXHu3DmuXr3Knj17aNy4MYsXL8bOzo5WrVoBqK7WJWpClHcaG9KOHTuYO3cuPXr0AODo0aNMmzaN8ePHl5lluiyXLl3C0tIyz3RyS0tLLC0tOXHihNrHFTZG4u7du5w7d04V7e7t7Y2TkxNdu3bl6NGjrFq1iqioKKZOnaqa7iBeHVlT3OPj4+nVqxdz5swhJSWFIUOG0LZtW+bOncvs2bMJDQ3F2NiYtLQ0BgwYwLBhw1SPFaK80tiQYmNjsbOzU33t5OTEs2fPuH//fpn8Zpq9iR4+fJiVK1eSkZGBoaGhan0/t8LGSJw6dQpXV1cMDQ0xNDTE2dlZdazAwEDc3Nxo06bNS6XsSh5S/kp6jJW67KPY2FgmT55Mr169sLKyUk03OXfuHE2aNOGTTz7h3LlzPH36lKlTp9K2bVvefffdEsnikbwfzeT8lC6NDSk9PR19/f920dfXL7O3f1tbW/PHH3+QkJCAiYkJLi4uuLi4cOfOHfz9/fONlihsjISurm6+U70fPHiAnp4eN27cICUlJc+digUleUjqlcZ7SLmzj+Li4nj//fdzRE3Y2NiwbNky2rdvz6lTp3BwcODNN9+kY8eOTJw4scTev5S8H83k/OSvpPKQys29WnXr1sXT05OpU6fy9OlTILPhhoeHo6urm2+0RGRkJIMHD8bV1ZU///zzuTESHTp04OjRo6SmppKQkEB4eLjqPYJp06YRGBhI+/bt1U5/FmVf9qgJBwcHHBwc+PTTTxk3bhwODg5ERkYSFBTEqlWruHHjBmvXrlXt9+eff5Z2+UKUqufeZbd//34qVaqk+jojI4NDhw7lyWnJ/kautpo1axZffvkl/v7+KBQKEhMTsbGxYe3atejp6amNlihsjISDgwMXLlzA29ub1157jZo1a2JkZMQXX3xBtWrVePfdd+nQoQPu7u68++67L/Q6JA9JvdLIQ8qdfZRf1MSpU6dyfD1+/HjGjx9frLUJUdboKDXElTo5ORXsIDo6fP/990VWVFl24cIFbt68ibe3N2lpafTp04d58+bRtGnTlz521mWztbX1Cy/3vcpkyUUzOT+ayfnJX0l979F4haQuE0hoZmFhwfLly/nyyy9RKpX06NGjSJqREEK86go8qUEUjKmpKevXry/tMoQQoswpNzc1CCGE0G7SkIQQQmgFaUhCCCG0gjQkIYQQWkEakhBCCK1Q7u6yO3z4MGvWrCE9PR2lUomXlxdDhgzBycmJjRs3Ym5uXqL1DB06lDlz5hRqNqDkIalX0nlIBclC8vT0BGDr1q0sW7aM06dPAzB27FgiIyOpXLkyAHv27Mkz+FeI8qZcNaS4uDhCQkIICwvDzMyMxMRE/Pz8sLCwKLWa1q5dW+jHSB6SeiU9y64gWUienp5cvHiR9evXk/0z6OfPn+fIkSNUr169xOoVQtuVq5+zHz16RFpaGsnJyQBUqlSJBQsW0KhRIwBWrFhBjx496NatG7/88gsAZ8+epW/fvnh7e9O1a1fVnLuYmBj8/Pzw8fHB0dGRr7/+GoBly5YRFBSEn58fTk5OrFy5EoD58+czefJkAPbt20efPn1QKBQ4OTlpHEUkyo733nuP4OBg1df6+vr8+++/BAQEsHjxYtX2jIwMrl27xrBhw+jYsSNffPFFaZQrhNYpV1dITZs2pWvXrjg7O9OsWTNsbGzw8PCgYcOGADRq1Ij58+ezefNm1q9fz9KlS9m8eTNz5szB0tKS06dPM2/ePJydndm5cycjR47Ezs6O27dv4+npSd++fQG4evUqW7ZsIT4+HmdnZ/r378/48ePx9vZm//79fPrpp2zYsAE9Pb0Xeh0SP5G/koyfUBc9AZCYmMiECRMYNGgQPj4+jB49mps3b5KYmMi5c+dITEykZ8+evP/++ygUCoYPH07FihXzjUApShKvoJmcn9JVrhoSZMaYjxw5koiICCIiIujduzehoaEAquyiRo0aceTIEQA++eQTTpw4weHDh/nll19ITEwEICAggB9//JHVq1cTExOT4xuhjY0NhoaGVKtWDVNTU+Lj46lXrx7z58/H19eXjz76SNUEX4TET6hX0kt2uaMnAG7fvo23tzcjR47E2tqar7/+muXLl5OcnMytW7fYtGkTixYtonXr1qr3j9zd3UlLSyv2OWoyq00zOT/5K6n4iXLVkMLDw0lKSsLNzQ0fHx98fHzYsWMHu3btAlBdsWQP8uvXrx82NjbY2NhgZ2fHpEmTABg3bhxVqlTB0dERNzc39u/fr3qMupwkgD///JOqVauWyF+sKHlxcXG8++67ObKQfvvtNwBu3ryJr68vixcvJjo6Gl9fX86fP09GRgYREREMGDCgNEsXQiuUq4ZkbGxMcHAwb731Fubm5iiVSqKjo2nWrJkqCym7x48fc/PmTbZu3YqhoSGhoaEoFAogMyfp0KFD1KpViy1btgCo/kyduLg4Fi9ezPbt2xk9ejQnT57E3t7+hV6HxE+oV9LxE7mjJ7JnIWW9l3To0CEqVKiQY79mzZrRv39/bG1tMTAwwN/fn+bNm5dY3UJoq3LVkGxtbRk9ejTDhw9XpcJ27tyZUaNGsW/fvjz7m5qa0qtXL7p3746+vj62trYkJyeTlJTEmDFj6NevH0ZGRjRt2pR69eppvDnho48+4n//+x/169fn448/5sMPP2Tv3r0v9DoM9Q0xMpD4idx+vfRrqS655JeFBPD6669z5swZ1ddTpkxhypQpJVWaEGWCxjwkoV0kD0kzeQ9AMzk/msn5yV9Jfe8pV7d9CyGE0F7SkIQQQmgFaUhCCCG0gjQkIYQQWkEakhBCCK0gDUkIIYRWKFefQwL4+OOPefDgAUuXLlVti4iIYObMmezZswcTE5NSrK5gJH5CvaKKn8gdKwEQFRXF1KlTCQ8Px9fXl9jYWCBzAoOtrS3btm0DMscXdejQgQULFuDi4vLStQhRnpS7hjRx4kQ8PDz4/vvv6dq1K0lJScyaNYt58+aViWYEEj+Rn6KaZZc7VmLhwoVs2rSJSpUqAaiaz6NHj3B0dOSzzz5T7Ttq1Kgco6eEEAVX7n7OrlSpEnPmzCE4OJikpCSWLl2Kk5MTNjY2OaIgoqKi8PPzA8DPz4+FCxfSp08f3nnnHU6ePAlkDlidM2cOffv2xcnJid27dwOZY4IGDx5M7969cXBwUH16PywsjPHjxzNo0CDeeecdZs2aVfInQBSapaUlYWFhebbPnDmTMWPGUKdOHQBCQ0Pp0KEDLVu2LOkShXgllLsrJIAOHTrQqVMnpk2bxo0bN9i5c+dzH5OWlsb27ds5fvw4S5YsUc2hi42NZevWrcTExODv74+Pjw/79+/H3d0db29v4uPjsbe3VzW3CxcusH//fvT09HBxcaFv375YWVkVqn6Jn8hfUcRP5I6VeP311/n9999V8READx8+5MCBA7z//vucO3eOs2fPcurUKQIDA9m7dy/Xrl2jRo0aL11LUZN4Bc3k/JSuctmQIPPqxsHBgRUrVmBsbPzc/Tt37gxA48aNefz4sWp7x44d0dHRoUmTJqrtgwcP5syZM6xfv55r166RlpbGs2fPAGjdurVqabB+/fo8efKk0LVL/IR6RbVkpy5Wolq1alSqVEm1/fPPP2fQoEG0b5+5vLdo0SLi4uKYOHEiv//+O7du3aJz5860atXqpespKjIaRzM5P/mT+IliZmJiQpUqVahXr16O7Vmj/dLT03Nsz5rflPv9AXXbFyxYwO3bt3F3d8fZ2ZlTp06pjptfNIUoW44dO0ZQUJDq661bt6p+P3DgQHx9fbWqGQlRFpS795A0MTMzU8VQfP/99y98nMjISAYPHoyrqyt//vkncXFxZGTIEtur5OrVq7zxxhulXYYQr5Rye4WkztixYwkODmb58uV06tTphY/zwQcfMGXKFIyNjalduzbW1tYaoykKS/KQ1CuqPKTcOUeQNz4iK3hPnQ0bNrx0DUKURxI/UYZI/IRm8h6AZnJ+NJPzkz+JnxBCCFGuSEMSQgihFaQhCSGE0ArSkIQQQmgFaUhCCCG0gjQkIYQQWqHcN6Q7d+7g5OSUZ7um+XKXL18mMDCwOMsSQohyRz4Y+wJatGhBixYtSu35JQ9JvaLIQ3peFtL9+/cZOnQojx49QqFQsHHjRiwtLQkNDeXrr79GV1eX6dOn4+3t/VJ1CFEeSUPSICEhgenTpxMXF8f9+/exs7Nj7ty5nD17luXLl7Np0yb8/Pxo0aIF586d4+HDhwQFBWFvb09MTIwq4uLhw4cMGzaMvn37smzZMuLi4rh16xZ3797lvffeY8SIEYWqS/KQ1CuK4arPy0KaMmUK/fv3p3fv3pw4cYLff/+datWqsXTpUq5fv05iYiKtWrWShiTEC5CGBNy/fx8vL68828PDw2nWrBlLly4lNTWV7t27qx0Zoy6aYufOnYwcORI7Oztu376Np6cnffv2BTLnoG3ZsoX4+HicnZ3p378/VapUKfbXKQovKwspKz4kMjKSt956C2dnZ15//XWWLFmCoaEhDRs2JDExkcTERHR15fJViBchDQmoWbMme/bsybHNysoKd3d3Ll26xIYNG7hx4waPHz9Wm7ejLpoiICCAH3/8kdWrVxMTE5PjcTY2NhgaGlKtWjVMTU2Jj48vVEOSPKT8vWwe0vOykP7880+ePHlCSEgIa9euZdy4cQwZMoRKlSrRuHFjMjIyGDhwoNbm6mhrXdpCzk/pkoakwaZNmzhy5Ai9e/emQ4cOxMTEqI2LUBdBMW7cOKpUqYKjoyNubm7s378/z/5ZjynsOEHJQ1KvKJbsnpeFVL16dcaOHUu1atXQ1dUlMDCQuLg4UlJSVAN0u3Xrhq+vryorSVvIrDbN5Pzkr6TykGRtQYPIyEj69OmDp6cnKSkp/P777wWOkYiMjGTs2LE4Ozvzww8/AKBQKIqzXFECOnXqxMGDBwH44YcfaN68OWZmZlSoUAEjIyOMjY0xNTXNEeIohCgYuULSYMCAAcyaNYs1a9ZgYmJC69atuXPnDg0aNHjuY8eMGUO/fv0wMjKiadOm1KtXr8giKCR+Qr2iiJ9QFz2R3aJFixgyZAgrV67ktddeY+vWrZiZmXHs2DFsbW3R1dWlU6dOvPPOOy9VhxDlkcRPlCESP6GZLLloJudHMzk/+ZP4CSGEEOWKNCQhhBBaQRqSEEIIrSANSQghhFaQhiSEEEIrSEMSQgihFaQhCSGE0Arl6oOx6enprF27lr1796Kjo4NCocDb25sPPvggx9if7L7++msA1WDU3JYtWwZkfhC2pCSlppCGfHwsN4vGjUlISS7w/no6ulTI9UHa7FETWbZu3cqyZcs4ffo0AIcOHWL27NkAtGnThhUrVuT770cIUXDlqiHNnj2bBw8esH37dqpUqUJCQgKjRo2icuXK9O/fX+1j8mtEpenrn06RkiFjiHJLSkyk4v/HRBTE0M5dc3ydO2oC4OLFi6xfv141bzA+Pp7JkycTHh5O9erVWbhwIQ8ePKBGjRpF8yKEKMfKzZJdbGwse/fuZcGCBarJ2iYmJsyYMYPq1asTEBBAWFiYav+sxNhly5axbNkyzp8/j5eXl+pXs2bNOHz4MACXLl3C19cXR0dH1RVTRkYGc+bMoXv37ri7u7NmzRog8yfwrCgDIM/zitKTFTWR5d9//yUgIIDFixertp06dYoWLVowceJEOnfuTK1ataQZCVFEys0V0qVLl7C0tOS1117Lsd3S0hJLS0tOnDih8fFt2rRRRVRs2LCBM2fO0K1bN65du8a///7Ltm3bSEhIwMnJif/973/s2bOHv//+m71795Kamoqfnx9NmjShQoUKL/1akpOSeKZIf+njvIqSEhMLvG9qSirnfv0v3yp71MTZs2eZMmUKo0eP5ubNm6r4iZ9++onvvvuOLVu2ULFiRYYMGULlypVp2LBhcbycIifxCprJ+Sld5aYhQc54iMOHD7Ny5UoyMjIwNDSkcePGBTpGZGQkO3bsYPv27arjde7cGUNDQ6pWrYqZmRlPnjwhKioKb29v9PT0qFChAh4eHpw+fRonJ6eXfh3GFSuiI0t2eRR2yc7QKP+oCYB//vmH5cuXk5yczK1bt9i0aRMuLi7Y2dnRrVs3AFxcXEhPTy8TM9BkVptmcn7yV1LxE+WmIVlbW/PHH3+QkJCAiYkJLi4uuLi4cOfOHfz9/XPkEqWlpak9xs2bNwkKCmLdunVUrlxZtV1f/7/TmHWc3DEVSqUShUKRJ/8ov+cSpat9+/aqdOCbN2/i6+vL4sWL+eeff/j111958OABpqamnDlzhqFDh5ZytUK8GspNQ6pbty6enp5MnTqV+fPnU6VKFdLT0wkPD0dXVxdTU1OuX78OwLFjx/I8PusGiMDAQCwtLZ/7fLa2tnz77bc4OjqSmprKvn37GD58OGZmZty+fZuUlBSePXvGuXPn6NixY6FeS992HTCQ+Ik8UlNSMTQq+HnRe07UhDo1atRg/vz5qiuk3r17Y21tXejjCCHyKjcNCWDWrFl8+eWX+Pv7o1AoSExMxMbGhrVr16Knp8e4cePw8PDA1tY2zxvVmzdv5t69e6xcuVJ144K3t3e+z9WnTx9u3ryJl5cXaWlpeHh4qDJy7O3t6d69O/Xq1XuhJYKKhkYSP6HGuV9/e+kll9dff50zZ85o3Obr64uvr+9LPY8QIi/JQypDJA9JM3kPQDM5P5rJ+cmf5CEJIYQoV6QhCSGE0ArSkIQQQmgFaUhCCCG0gjQkIYQQWkEakhBCCK0gDen/zZ49Gy8vL9zc3LC2tlYNUd26dasqgqKwAgMDuXz5MpcvXyYwMLCIKxZFKSoqCgcHBwCuXLlCp06d6NixIyNHjkShyBzTdOjQIWxtbbG1tWXkyJHIJyaEKFrl6oOxmsycORNANUooa5Dqy5g7d67q9y1atHjp42WRPCT1CpqHlDsHKXfsxPTp05k3bx5dunRh4MCB7N27F2dnZ4mdEKKYSUN6juwBfJs3b2bPnj08e/YMAwMDFi1axBtvvIGTkxOenp5ERETw7NkzQkJCsLa2xs/Pj9GjRwOwfPlyNm3ahJ+fHy1atODcuXM8fPiQoKAg7O3tC1WT5CGpV9DhqrlzkLJiJ7JiQXbv3o2enh6pqanExsZSq1atHLETN27cYMiQIdKMhChismRXQAkJCRw7doxNmzaxf/9+HBwc2LJli+rPTU1N2bVrF76+vqxevVrjsdLS0ti+fTvTpk1jyZIlxV26eA4fHx8MDAxUX+vp6XHr1i2aN2/OgwcPsLKy4sGDB5w4cYKQkBAOHTrE4sWLiYmJKcWqhXj1yBVSAZmYmLBo0SIOHDjAzZs3+fHHH2nWrJnqzzt37gxA48aNOXr0qMZjZd/38ePHha5F8pDyV5A8pNw5SAD37t1TZR5l2bZtG99++y0DBgygW7duNGnShLt37wLQtGlTwsLCVPMJywrJ+9FMzk/pkoZUQH///Td+fn68//77dOnSherVqxMdHa3686z5Ttkzl/JTmH3VkTwk9Qq6ZKcpB6lt27Z4enqyaNEiGjduzPXr17lz5w6+vr58+umnNGzYEFNTU27cuEFgYGCZmvQts9o0k/OTP8lD0jKXL1+mYcOGDBw4kOTkZJYuXUrt2rVLuyxRDAICAhg4cCCGhoZUrFiRdevWSeyEECVAGlIBdezYka+//ho3NzeUSiXt2rXj2rVrpVKL5CGpV9A8JHU5SNkjJjp06EBkZGSefSR2QojiJfETxahHjx4EBwcX2S3fEj+hmSy5aCbnRzM5P/mT+IkyrlevXhgbG2NlZVXapQghRJkgS3bFZNeuXaVdghBClClyhSSEEEIrSEMSQgihFaQhCSGE0ArSkIQQQmgFaUhCCCG0gtxl9/8OHz7MmjVrSE9PR6lU4uXlxZAhQ3BycmLjxo2Ym5sXy/N6eXkVOupC4ifUK0j8RO7oCcjMQpo6dSrh4eFcuXKFYcOGoVQqadmyJcuWLUNPT48VK1awYcMGdHR0mDFjBu7u7sX5UoQol6QhAXFxcYSEhBAWFoaZmRmJiYn4+flhYWFR7M/9IrlLEj+hXkFm2eWOnihIFlLnzp35/PPPuXjxIsnJybz55pt07979hWcRCiHUkyU74NGjR6SlpZGcnPnTdaVKlViwYAGNGjUCYMWKFfTo0YNu3brxyy+/AHD27Fn69u2Lt7c3Xbt25dixY0DmHLQ5c+bQt29fnJyc2L17N5CZp7R48WIAVq1axYcffgggH5wtZVlZSFl2795Nly5dcmQhVa9enV9++QUDAwNiY2MxNTWVZiREMZArJDKjBLp27YqzszPNmjXDxsYGDw8PGjZsCECjRo2YP38+mzdvZv369SxdupTNmzczZ84cLC0tOX36NPPmzcPZ2RmA2NhYtm7dSkxMDP7+/vj4+DBr1iy8vb1p1qwZO3bsyPFNsLAkfiJ/z4ufyB098frrr/P777/niJ74+++/GTlyJCYmJjx79ky1ffv27axZs4Y+ffqU2ZiCslp3SZHzU7qkIf2/2bNnM3LkSCIiIoiIiKB3796EhoYCqBpNo0aNOHLkCACffPIJJ06c4PDhw/zyyy8kZvtG2LFjR3R0dGjSpIkq76hatWoEBAQwduxYVq9ejamp6QvXKvET6hVkye550RNZ3N3dWbduHRs3buSrr74CoG3btsyZMwdXV1eePn2Ko6Nj0b+IYiSz2jST85O/koqfkCU7IDw8nIMHD1KrVi18fHz47LPPCAoKUo3/0dPTA3LmF/Xr149Lly5hbW3N8OHDcxwvv7yjGzduUK1atRL5ixUvxtPTUzXFvXLlyujq6nL16lV69uyJUqnEwMAAIyMjdHXlv44QRU2ukABjY2OCg4N56623MDc3R6lUEh0dTbNmzbh+/Xqe/R8/fszNmzfZunUrhoaGhIaGolBovmKJjo7mm2++ISwsjH79+uHs7EzTpk1fqF6Jn1CvIPET6qInslOXhVSnTh1atmyJnZ0dOjo6uLq6Ym9vX5SlCyGQhgSAra0to0ePZvjw4aSlpQGZMeOjRo1i3759efY3NTWlV69edO/eHX19fWxtbUlOTiYpKUnt8dPS0ggICGDatGnUrl2bKVOmMHXq1BcewFrR0EjiJ9Q49+tvL7TkUpAspJkzZzJz5syXrlEIkT/JQypDJA9JM3kPQDM5P5rJ+cmf5CEJIYQoV6QhCSGE0ArSkIQQQmgFaUhCCCG0gjQkIYQQWkEakhBCCK1QLhpSVFQUfn5+ObZdvnzp4nQQAAAgAElEQVSZwMDAIn2e77//niVLlhTpMUXxiYqKwsHBAYCLFy/SuXNnHBwc6NatG3FxcQCMHTuWtm3b4uDggIODA0+ePCnFioV4tZXbD8a2aNGCFi1aFOkxu3btSteuXZ+/40uSPCT1NOUh5c5Byh078eGHH7Js2TJatWrF6tWrCQkJ4dNPP+X8+fMcOXKE6tWrl8hrEKI8K7cNKSoqiuXLl7Np0ybOnj3LZ599RnJyMk+fPmXatGk4Ozvz4MEDAgMDuXfvHvr6+owfP54uXbqwbNky4uLiuHXrFnfv3uW9995jxIgRhIWFcfbsWRYsWICTkxOenp5ERETw7NkzQkJCsLa2JiYmhoCAABQKBW+//TY//PAD3333XaFqlzwk9TQNV82dg5QVO5F15bxt2zbq1KkDQHp6OsbGxmRkZHDt2jWGDRtGXFwcgwcPZtCgQcX7IoQox8rFkt3zZEVJfPPNN8yZM0e17BYcHIytrS379u1j6dKlTJ8+nQcPHgBw9epV1q9fz86dO1mzZg1Pnz7Nc1xTU1N27dqFr68vq1evBjJnpX344Yfs2bOH+vXrP3cGnigePj4+GBgYqL7OakanTp1i+fLljB8/nsTERMaMGcPmzZs5fPgwn3/+OZcuXSqtkoV45ZXbK6Ts8ouSOHPmDHPmzAGgfv36tGzZUhXQZ2Njg6GhIdWqVcPU1JT4+Pg8x+3cuTMAjRs35ujRozx+/Ji7d++qBnP6+PiwcePGQtcreUj5yy8PKXcOEsC9e/dy5CAdPXqUL774gtDQUP766y8UCgVdunQhOjoagDfffJNvv/1WNe+wLJK8H83k/JQuaUhkRknY2NhgY2ODnZ0dkyZNAiD3mD+lUqm6osk+z0lHRyfPvtn3yYqh0NPTU7tfYUkeknqaluyel4O0efNmDh48SFRUFFWrVgUyJ7QPHTqU8+fPk5GRwfXr15k6dSrNmzcv9tdSHGRWm2ZyfvIneUglJCtK4sMPP6RLly58//33qqZja2urmsh9+/Ztzp8/T6tWrV74uSpXrkz9+vU5efIkgNpJ4qLkKRQKxo4dS3x8PD179sTBwYGZM2fSrFkz+vfvj62tLfb29vj7+5fZZiREWVBurpB+/vlnWrdurfq6Vq1a1KhRQ2OURGBgIDNmzFDFjc+ZM4eaNWu+VB0LFy5k+vTpLF68GCsrK4yNjQt9DMlDUk9THpK6HKTssRMPHz5U+7gpU6YwZcqUoitSCJEviZ8oYcuXL6d3797UrFmTo0ePsm/fPpYtW1agx0r8hGay5KKZnB/N5Pzkr6S+95SbKyRtUbduXQYNGoS+vj5VqlRh7ty5pV2SEEJoBWlIJaxnz5707NmztMsQQgitU+5vahBCCKEdpCEJIYTQCtKQhBBCaAVpSEIIIbSCNCQhhBBaQe6yKyJZk7719PTw9fUlKSlJNU08MDAQX1/fIou7kPiJnHJHS6SkpPC///2PGzduUKVKFVasWEFsbCyTJk1CR0cHNzc3ZsyYUYoVCyHUkYZUxLI+VxQVFZVnW1GR+ImcckdLrF27FhMTE86cOcPVq1cZPXo0Dx48YNeuXVhYWODo6IiHh0eOyR1CiNInDamI+fn5MXr06Hy3rV69GmNjY/744w+srKwIDQ3FUMYAFakrV67g6uoKgJWVFdHR0dy4cQN9fX0SEhJ48uQJ1apVK+UqhRC5SUMqYRcuXODQoUPUrFmT3r17ExERgZOTU6GOIfETOWWPljh37hxmZmZs2LCB+vXr8+uvv3L37l3Onz/PlStXmD59OhYWFty+fZt//vmnlCsveRKvoJmcn9IlDamENW7cmNq1awOZqaVPnjwp9DEkfiKnrGiJrFlkLVu2ZPLkyUyaNImOHTvStm1b2rdvT/v27Rk4cCBBQUEcPXqU2bNnl3bpJUpmtWkm5yd/Ej9RBvz888/ExcUBmVlJenp6z31MQXKUxMv56aef6NSpE+Hh4Xh7e2NhYUHnzp159OgRkBkDoqsr//SF0DZyhfQSdu/ejbW1Nf379+fq1avUr1+fv/76q9ifV+IncsodLdG4cWM++ugjQkNDMTU1Zf369fz000+4urpiZGREnTp1WLduXSlVK4TIjzSklzBs2DCmTJnC5s2bqV27NosXLyYyMrLYn7eioZHET2hQvXp1jh07lmObl5cXXl5epVSREKIgJA+pDJE8JM3kPQDN5PxoJucnfyX1vUcW0oUQQmgFaUhCCCG0gjQkIYQQWkEakhBCCK0gDUkIIYRWkIYkhBBCK8jnkLJJT09n7dq17N27Fx0dHRQKBd7e3nzwwQfo6OiUdnkqD5OT0c/IKO0ytIaBri6m/38rqrroicaNG6NQKOjTpw9DhgzBxcWllCsWQqgjDSmb2f/X3p3H5ZT3fxx/lSkhJhLGFpqyL3EzsrXgQSpLRtbsQ9ZhDJFsUSNjGbqzjBk7N26yDrKNLTTDLRqEQUa3O4xCWdJyfn80nV9R14R0Hfo8H495PLrOdZ3v+Vxf8+jTdc65vu8ZM/jzzz/ZtGkTJUqUIDExkREjRlC8eHF69+6t7/JU/Q8e5EGKLK6aYW/HjurP2UVPLF68mH79+nH79m0GDx6sx0qFELrIKbu/xMbGsnPnTmbPnk2JEiUAMDU1ZerUqZQuXZqrV6/i6elJ165dcXR05F//+hcAQUFB+Pr64unpiZOTE0uWLAEgKioKDw8P3N3d6dmzJ9HR0UB6HEKGkJAQJk6cmL9v9AOXXfREYmIiy5cvx9HRUc/VCSF0kU9If7lw4QJWVlZ8/PHHWbZbWVlhZWWFv78/w4cPx87Ojtu3b9OxY0d69uwJwJUrV1i/fj0JCQm0adOG3r17s3r1agYMGICzszPbtm0jIiKCKlWq5Emtz5495Wlycp6M9SF48SKJs5cuAWQbPZGUlERKSgoPHjzg2rVrWFhY6Lli/ZF4Bd1kfvRLGlImma8T7du3jyVLlpCWloaxsTGbN2/m+PHjLFu2jKtXr/L06VP1tZ999hnGxsaYm5tjZmZGQkIC9vb2+Pn5cfz4cZycnPL0r/MiRYpS1EhO2WUwNi6sxk/MmDEj2+gJAHNzc6ytrQvs8jCyNI5uMj85k/iJfFanTh2uX79OYmIiAO3bt2fHjh0sWbKE+Ph4xowZw4EDB7CysmLMmDFZ9s0uUqJ9+/Zs27aNevXqsWrVKqZNm6a+JmP5wBS5DpTnXo6eqFatmr5LEkLkkjSkv5QvX56OHTvi7e3N48ePgfSGceTIEQwNDQkLC2P06NG0adOGY8eOAZCamnNI3pgxY4iMjKRHjx58+eWXXMp0SunatWsoisLhw4ff/RsrYKytrVmyZAl2dnZMmTKF+fPn67skIUQuySm7TKZPn87KlSvp27cvqampPHnyhM8++4zly5dz5MgRevXqReHChalRowYVKlQgJiYmx7G8vLyYPHkywcHBGBkZMX36dADGjRuHl5cXpUuXplGjRmpo3OtY1aYNH0keksooU9hedtETGVatWpVPFQkh3oTET7xHJH5CN7kGoJvMj24yPzmT+AkhhBAFijQkIYQQmiANSQghhCZIQxJCCKEJ0pCEEEJogjQkIYQQmiANSQghhCYUqC/GhoeHM27cOHbs2IG5uTkAP/zwA+fPn+f58+fMmjWLsmXLZrtvZGQkGzduxN/fn8mTJ9OjRw/q1q2bn+WrCmoeUubco1WrVqlfdH3+/DkREREsX74cb29vXrx4QeHChdm4caP67yyE0L4C98XYwMBAoqOjWbJkCefOncPb25stW7aokRNalvHlNJ/o6AKZh7S3Y0csihR5ZfuIESOoX78+y5cvJygoiKZNm7J161bKly+PnZ2dHirVJvnip24yPzmTL8a+I2PHjuXOnTusWbMGb29vAgMDKVGiBE5OTsTExBASEsLYsWMZOHAgbdu2VZf8CQ8Px9PTEwBPT0/Cw8NJSUnB19eX7t2707p1a4YPH87z58+JiYmhc+fOjB8/HldXV/r168fDhw8B2LNnD+3bt8fd3Z3JkydLHtJbOnPmDBcvXsTT05O4uDh27dqFg4MDp0+fVlf5FkK8HwrUKTsAY2Nj5s6dS6dOnRgyZAi2travvObcuXPs3r2bQoUK0b59ezX3KLvXGRkZsWnTJtLS0ujXrx9Hjx6ldu3aREVFERAQQK1atRg1ahS7du3CxcWFgIAAtm7dioWFBaNHj8bU1PS130NBzUPKnHuUYcKECfTs2ZMjR45w48YNKleuTJcuXZg5cyYzZsygU6dOeqpWmyTvRzeZH/0qcA0J4D//+Q8lS5bk1KlTjBw5ko8+yjoNtra2aqOoVKkSjx49ynacxo0bY2Zmxvr167lx4wbR0dFqTpK5uTm1atUC0legfvToEWfOnMHW1la9TtW5c+ccFwLVpaDmIWXkHmV4+PAhsbGxDB06lGfPnlGsWDGGDh0KQP/+/Tlw4ICcgslETknpJvOTM8lDekd+//13goKC2LhxI8bGxmrkeGbZ5Rtl59ChQ3z99deYmJjg7u5O48aN1ddmN4ahoSFpBfBmhHfl2LFjtGnTBoAiRYpQuXJljh8/rj5Xu3ZtfZYnhHhNBeoTUlJSEmPHjmX8+PFUqlSJ2bNn4+7uTsuWLd9ovFOnTuHs7EzXrl25ffs24eHhOi+iN2zYED8/P+7du4eFhQV79ux5owuEBTV+InPMBKRHx2cO4JsyZQqTJk0iJSWFqlWrEhgYmN8lCiHeQoFqSAEBAVhbW6vXFSpUqMCkSZMYP348T548ee3xunXrxtdff81PP/2EkZERDRs21JmRVKpUKXx9fRk4cCDGxsZUrFjxje7uK2ViIvETwPjx47M8trGx4cSJE3qqRgjxtgpUQ5oxY8Yr2zp37kznzp3VxxUrVsTd3V19vHbtWgAOHjxI0aJFs2wD2LVrV7bHypwGO2rUKADi4+OJiopi586dGBoaMmvWLCwtLd/iHQkhxIejQDWkN7Vnzx78/f3x8fF5q3HMzMx4/Pgxrq6uFCpUiNq1a+Ph4ZFHVQohxPtNGlIudOjQgQ4dOrz1OAYGBvj6+uZBRUII8eEpcHfZCSGE0CZpSEIIITRBGpIQQghNkIYkhBBCEwrsTQ0xMTG0bt2aFStW0Lx5c3W7k5MTCxcuVKMm8kqnTp3YsWNHnoxVEOMnMkdPQPbxEzNnzsTDw4NKlSoB6bf529vb66NcIcQbKLANCcDIyIgpU6awc+fOLIuclixZMk+bEZBnzQig/8GDBS5+Ym/Hjlke9+/fn/79+wPp8RMDBw4kPDycOXPm0LVrVz1UKIR4WwX6lF2ZMmVo1qzZK0vM/PLLL1miJubMmUP37t1p27YtR48eBSA2NpY+ffrg5ubGuHHjaNWqFZD+JdjvvvsOgKVLl/Lll18CUL16dQDu3r3LoEGD8PDwwMHBgYULF+bLe/1QZcRPDBkyhKioKFasWEHLli0ZN24cKQWsaQvxvivQn5AAJk6ciJubG2FhYVlO3WWWnJzMpk2bOHz4MAsXLsTe3h5/f3+cnZ3p3bs3Bw4cYPfu3QBMnz6dLl26ULNmTTZv3kxISEiWsXbv3o2rqytdunQhISEBe3t7PD09KVWqVK5rLojxE9lFT8D/x0+cPXuWJk2a4ODgQIUKFQgICMDHx4fu3bvroVrtkngF3WR+9KvANyRTU1NmzpypnrrLTsbiq9bW1mrQXlhYGN988w0Abdu2VdekMzc3Z+LEiYwePZply5ZhZmaWZaxBgwZx+vRpfvzxR65du0ZycjLPnj17rZoLYvzEy9ETkDV+AiAhIQEHBwcABg8ezNatWyVOIBOJV9BN5idnEj+Rj1q0aJHtqbsMGQuZGhgYqNsKFSqUYyzFjRs3MDc3z/YfcPbs2axdu5by5cszbNgwSpYsmeM4QrfM8ROKotCjRw91cdtDhw7JLxch3jMF/hNShoxTd/fv38/V6+3s7Ni1axe9evXi6NGjPH78GIDLly+zbds2QkJC6NWrF23atKFGjRrqfmFhYcyYMYOGDRty5MgR7t69+9oZSQUxfuLl6AnIGj9hYGDAlClTcHd3p0iRItSqVYsvvvgiv8sUQrwFaUh/yTh1N2jQoFy9fvLkyXh7e7N582Zq1KhBiRIlSE5OZuLEiUyaNIly5coxYcIEvL292bJli7rf0KFDmTBhAiYmJpQrV446deoQExND5cqVc12rxE+kezl+omnTpowYMUJP1Qgh3paBIueL3siaNWto1qwZn376KRcvXmTKlCmv3MCQ1zLO49apU0caUjbkGoBuMj+6yfzkLL9+98gnpDdkaWnJV199haGhIYULF2bmzJn6LkkIId5r0pDekL29vawCIIQQeUjushNCCKEJ0pCEEEJogjQkIYQQmiANSQghhCbkW0PKWFw0P4/38neK4uLiqF27NkFBQflSQ0hICBMnTgTgiy++4O7du/ly3IJg1apVODg44ODgQNOmTTExMeHw4cNYWVmp2zMWwhVCvB8+6Lvsbt68ycOHD9X15Pbv36+uOZffli9fnmdjSR6SxE8I8SHK94YUHh7OsmXLMDEx4fr161SvXp25c+dy7949Ro4cibW1NZcvX8bc3JyFCxdiZmbGsWPHWLRoESkpKVSsWJGZM2dSsmRJnJycqFevHpcvX2bDhg2Ym5tnOVbr1q05dOiQ+gtq3759tG3bVn0+IiICf39/kpKSKFmyJH5+flhaWuLp6UndunU5e/YscXFx+Pr6Ym9vT2xsLF9//TWPHj3CxsaGX3/9lWPHjvHs2TN8fX25cuUKBgYGDBo0iM6dO2epxcnJiTVr1mBmZoaPjw93797l3r172NnZ4e/vn2WdvL8jeUj/LyN+Ijg4mNWrVxMbG8t3331HkyZNCAwM5KOPPui/uYT4oOjlGtK5c+eYOnUqe/fu5c6dO5w4cQKAqKgoBgwYwO7duylRogS7du0iLi6OefPm8eOPP7J9+3ZatGjB3Llz1bFatWpFaGjoK80IwNnZmdDQUAD+/PNPACwsLAB48eIFX331lbrKd48ePfjqq6/UfTMiJyZNmqRmFmVETuzatYv27durp+CCgoIoWbIku3fvZvXq1QQFBREVFZXtez9y5Ag1a9Zk06ZNhIaG8uuvv3Lx4sW3ndICKyAggGnTpgHQpEkTgoKCOHbsGImJiSxdulTP1QkhXode/ny0tramXLlyAFhZWfHo0SMgPbqhVq1a6msePXrE+fPn+d///kffvn0BSEtL4+OPP1bHql+/fo7HsbW15ebNmyQkJLBv3z7atWunNqbo6GhKlChBvXr1gPTmNXXqVBISEoDXi5w4ffo0AQEBAJQqVYrWrVvzyy+/ZEmhzeDq6sqFCxdYtWoVN27c4OHDhzx9+vS15k/ykNIlJCQQERFBiRIlOHv2LJ06dSI+Pp74+Hhq1arFgQMHsLOz01PF2iR5P7rJ/OiXXhpS5rWQDAwM1PiF7LanpqbSsGFD9a/dpKQknjx5ku1YLzMwMMDR0ZFDhw4RGhrKwoULWb9+PUC2K2xnHC/zuLmJnHh5W+ZxXrZ27VpCQ0Px8PCgWbNmXL169bXjJyQPKd3OnTtxdXWlUaNGKIrCJ598wpkzZ6hYsSIbNmygXbt2sjZZJrJWm24yPzmTPKS/1K9fn4iICG7evAnA4sWLmTNnTq73d3Z2ZsOGDRgbG2dJZa1WrRoPHz7kwoULAOzZs4fy5cu/EqiXWUbkBJAlcqJp06bqit5xcXEcOnSIJk2aZDtGWFgY3bt3p2PHjiQlJREVFfXa8RMiXU7xE/b29jx9+lTiJ4R4z2j+iq+FhQUBAQGMGTOGtLQ0ypYty7fffpvr/Rs0aMD9+/fp1q1blu3GxsYsWLCAmTNn8uzZMz7++GMWLFigc6zsIicg/S6v6dOn4+bmRmpqKl5eXtSuXZsrV668Mka/fv2YPn0633//Paamptja2qqhcrkleUjpJH5CiA+LxE+8Bn1ETmQm8RO6ySkX3WR+dJP5yZnET2iQRE4IIcS7Iw3pNUjkhBBCvDuav6lBCCFEwSANSQghhCZIQxJCCKEJ0pCEEEJogjQkIYQQmlBgG9LTp0/55ptvaNeuHR07dqR3796cPn0aSP8CbGRk5BuN+7q5T29yrLjnz7n/7Nlb/fcwKemVccPDw3FwcADSV0Jv2rQpLVq0YODAgbKahBDinSuQt30risKIESOoVq0au3fvxsjIiEuXLjF06FAWLFiAv79/vtXyJsfKi/iJl+Mc5syZw9q1aylWrBgAM2bMYOrUqXTo0IHevXvz008/4ebm9lbHFEIIXQpkQzp79iw3b97k+++/x8jICIBatWrh5eVFcHAwKSkpjBw5EiDb7CZjY2PWrFnDunXrKF68ONWqVaNy5cqMGjUKgKlTpxIREQGkR1NYWlqyd+9eVq5cyfPnz3nx4gUBAQE0bNgQT09PRo4cyWeffaafyfiLlZUVISEheHp6AukrpcfFxaEoCgkJCeo8CSHEu1IgG1JkZCQ1a9Z85ZdskyZNmDdvHrVr11a3nTt3jr1791KmTBk8PDw4ceIE5cuXZ/369YSEhGBkZISnpyeVK1dW92nWrBl+fn4EBgayceNGxo8fz8aNG1m6dCmlSpViy5YtfP/992+c15MX8RMvxzlUqVKFqKgonjx5wtmzZylUqBAjRozA19cXU1NTNeJB696HGvVJ5kc3mR/9KpANSVGUbBNanz9//koURHbZTbdu3cLR0VHNO3JxcVFX/gZo06YNAJ9++ilnzpzB0NCQ4OBgDh8+zM2bN/nll18wzGax0NzKi/iJ7OIczM3NKVasGI0aNcLZ2ZmTJ09Su3ZtgoODWb9+PcHBwW91zHdN1iLTTeZHN5mfnEn8xDtUr149Ll68SPJfnzIyTk2dP38+y6cjyD6jydDQUOdF/ozY7IzXP3nyhM8//5yYmBgaN26snhbTslKlSqmrmZcvX574+Hg9VySE+NAVyE9IjRo1wsrKisDAQLy9vdm2bRsHDhzgjz/+YN68eSxevFjn/nZ2dowaNYrRo0djbGzM/v37dSaTRkdHY2BggJeXF4qiMGHChBwD/HIjL+InsotzyOyHH36gR48efPTRRxgbG7N8+fK3Op4QQvydAtmQDAwMCA4OZt68ebi4uGBkZESJEiWoXLkyx44d48WLFzr3t7GxoW/fvnTv3p2iRYtSsmRJnUuy16hRg5o1a+Ls7IyBgQEtWrR4q3PVpUxM3skS8FWqVFFvfW/RogVhYWF5fgwhhMiJ5CFlkpaWxtGjR3FwcMj2GlOGmzdvcvToUfr37w/AsGHD6NatG05OTu+0PslD0k2uAegm86ObzE/OJA9JDwwNDXF0dPzb11WoUIHIyEhcXV3VTzy52U8IIUTOpCG9AWNjY+bNm6fvMoQQ4oNSIO+yE0IIoT3SkIQQQmiCNCQhhBCaIA1JCCGEJkhDEkIIoQnSkIQQQmiCNCQhhBCaIA1JCCGEJkhDEkIIoQnSkIQQQmiCNCQhhBCaIA1JCCGEJkhDEkIIoQnSkIQQQmiCNCQhhBCaIA1JCCGEJkhDEkIIoQmSGPseURQFgBcvXui5Eu1KSkrSdwmaJvOjm8xP9jJ+52T8DnpXDJR3fQSRZxISErh69aq+yxBCFFA2NjYUL178nY0vDek9kpaWxpMnTzAyMsLAwEDf5QghCghFUUhOTqZYsWIYGr67Kz3SkIQQQmiC3NQghBBCE6QhCSGE0ARpSEIIITRBGpIQQghNkIYkhBBCE6QhCSGE0ARpSEIIITRBGpIQQghNkIb0Abh06RL9+/fXdxma8+uvvzJhwgTGjx/Pv//9b32XoznXrl1j9OjRTJw4kbCwMH2Xo0mpqal4enoSGRmp71I058aNG7i7u/P111+zatWqPBlTFld9z92+fZsjR45QqFAhfZeiOY8fP8bPzw9jY2OGDx9Ot27d9F2Spjx9+hQfHx8KFSrE/Pnzad68ub5L0pylS5dSpkwZfZehSWfPnqVcuXKYmJhga2ubJ2PKJ6T3XKVKlRg+fDgffSR/W7ysdevWGBkZMXfuXPr27avvcjSnfv36PH/+nFGjRtGyZUt9l6M5oaGhWFtbU6VKFX2XokmNGjVi1qxZTJ06lUWLFuXJmNKQxAfr8ePH+Pr64uzsTLNmzfRdjub89ttvlC5dmo0bN7JlyxZ9l6M5oaGhnDhxgp9//pk1a9bouxzNuXDhAsnJyRgbG+fZH8TyZ7X4YM2aNYvY2FhWr17NJ598wrhx4/RdkqYkJSUxefJkTE1Nsbe313c5mjN//nwAgoKCcHBw0G8xGlStWjVmz56NqakpHh4eeTOoIjQpISFBcXFxUW7fvq1u27lzp+Ls7Ky0bdtWWbdunR6r0y+ZG91kfnST+dFNn/MjDUmDIiIiFFdXV6V27drq/xSxsbGKo6OjEh8frzx58kRxc3NTrl27pudK85/MjW4yP7rJ/Oim7/mRa0gatHnzZqZNm5bl7p6TJ0/StGlTzMzMKFq0KO3atWPfvn16rFI/ZG50k/nRTeZHN33Pj1xD0iB/f/9Xtt27dw8LCwv1cZkyZbhw4UJ+lqUJMje6yfzoJvOjm77nRz4hvSfS0tKyxJYriiIx5n+RudFN5kc3mR/d8nN+pCG9J8qVK8f9+/fVx/fv35cv7P1F5kY3mR/dZH50y8/5kYb0nmjWrBmnTp0iLi6OZ8+esX//flq1aqXvsjRB5kY3mR/dZH50y8/5kWtI74myZcsyduxY+vbtS3JyMp9//jn16tXTd1maIHOjm8yPbjI/uuXn/BgoiqK8k5GFEEKI1yCn7IQQQmiCNCQhhBCaIA1JCCGEJkhDEkIIoQnSkIQQQmiCNCQhhBCaIA1JiJc4OTnRvXt3Xv5GRHh4ONWrVyclJSXPj+np6cmCBQvyfNzcio2Nxc3Njbp167Jp0ya91fGymJgYqlevznsIoj0AAAc7SURBVK1bt/RdisgH0pCEyEZERASbN2/Wdxn55scff8TAwIA9e/bg4uKi73JEASUNSYhsVKhQgfnz5xMXF6fvUvJFYmIi1tbWVKpUCVNTU32XIwooaUhCZKN///4UK1aMb7/9NsfXVK9enZMnT6qPQ0JC1DW+wsPDadWqFVu3bqV58+Y0btyYFStWEB4eTvv27bG1tWXSpEmkpaWp+9+7dw9PT0/q1q1L9+7diY6OVp9LSEjA29ubRo0a0bx5c6ZMmUJiYmKWY/n5+dGoUSOCgoJeqTUtLY0ffviBNm3aUK9ePfr06UNUVBSQfrowJCSE3bt3U7169Vf2zThttnPnTlq1asU//vEP/Pz8SE5OVl9z5swZdUkZFxcXtm/fnmWMkJAQOnToQL169XB3dyc8PFx9zsnJiVWrVtGpUycaNGjA4MGDuXv3brZzrmsexPtPGpIQ2ShSpAg+Pj5s27aNs2fPvtEYDx48IDQ0lDVr1vDFF18wd+5cAgMDCQwMZM6cOezcuZMjR46or9++fTvt2rVj+/btVKxYkYEDB6rXq3x8fIiPj2f9+vUsW7aMmzdvMmnSJHXfu3fvkpiYyLZt2+jSpcsrtQQHB7NixQomTZrEtm3bqFixIoMHDyYxMZGgoCCcnZ1p164dJ06cyPH9BAcHM3/+fIKDgzl48CDfffcdkL7685AhQ3Bzc2PXrl2MGDGCWbNmcfjwYSC9Gfn5+TFkyBB27NhB8+bNGTJkCHfu3FHHDgoKYsCAAWzevJmkpCRGjRqVbQ1/Nw/iPfdOcmiFeI85OjoqmzdvVhRFUYYOHaq4ubkpycnJyunTpxUbGxslOTlZURRFsbGxUcLCwtT9tm7dqrRs2VJRFEV9bUbUc0JCgmJjY6Ns2bJFfb2bm5uyfPlyRVEUpU+fPsrIkSPV5xISEpQGDRoohw8fVm7duqVUr15diY+PV5+PiYlRbGxslDt37qjHunLlSrbvJy0tTWnSpImyfv16dduLFy8Ue3t7Zd26dYqiKIq3t7cybty4bPe/ffu2YmNjo+zfv1/dtmXLFqVJkyZKamqqsmDBAsXLyyvLPkFBQUrfvn0VRVGUzp07K3PmzMnyvIeHhzJ79mx1vmfOnKk+98cffyg2NjbKpUuX1GNHR0f/7TyI95+s9i2EDr6+vri4uLB27Vpq1ar12vtXqlQJABMTEwDKly+vPmdiYsKLFy/Ux3Xr1lV/NjU1pWrVqly/fh1ID0VzdHR8Zfzo6GgMDdNPdFSoUCHbGh48eMDDhw+pX7++us3IyIg6deqo4+eGra2t+nOdOnV4+PAhf/75Jzdu3OD48eNZnk9JSaFUqVIAXL9+nWHDhmUZq0GDBty4cUN93LBhQ/XnSpUqYWZmxvXr12nQoIG6/fr16zrn4ZNPPsn1exHaJA1JCB0qVqyIl5cXQUFBTJ8+XedrU1NTX9lWqFChLI8zmkd2Xk7hTEtLw8jIiNTUVIoWLfrKdRkACwsLIiMjAShcuHC24+a0PTU1Nduac5L5vWRc+zI0NCQlJQUXFxeGDx+e5fUZ7zWjGes69svzlJqa+spc/d08iPefXEMS4m8MGjSIMmXKqNdMMhgZGWW5oH779u23Os7Vq1fVnx8/fkx0dDRWVlZUrVqVp0+fkpqaiqWlJZaWlgB88803ubqgX7x4cSwsLDh//ry6LTk5mYsXL1K1atVc15dxEwTAb7/9RunSpTE3N6dq1apER0ertVlaWnLixAm2bNkCQLVq1bIcG+D8+fNZjn358mX151u3bpGQkPDKDRZvOw9C+6QhCfE3jI2NmTZtGv/973+zbK9bty4rV64kOjqan3/+mZCQkLc6zt69e9m0aRO///47Pj4+VK5cmWbNmmFlZUXLli2ZMGEC58+fJyoqCm9vbx48eJDrKOmBAwfyz3/+k0OHDnH9+nWmTp1KUlISrq6uua4vICCAyMhITp06xaJFi+jVqxcGBgb06tWLy5cvM2/ePKKjo9m3bx/ffvstZcuWBWDAgAFs2LCB7du3c/PmTebNm8fly5fx8PBQx163bh0HDx4kKioKHx8fmjZtipWVVZbj58U8CG2ThiRELtjZ2b3yy3vKlCnqL/Vly5bx5ZdfvtUxMm6/7tKlC48fPyY4OFg9bTVnzhwsLS0ZOHAgffr0oUyZMixevDjXY/fv358ePXowbdo03N3duXPnDmvXrqV06dK5HsPFxQUvLy/Gjh1L165d1etCFSpUYNmyZZw8eRJXV1cCAwMZNWoUvXr1AqBdu3aMGzeORYsW0bFjR8LDw1m5ciXW1tbq2F26dGHhwoX07NkTCwsLFi5cmG0NbzsPQtskMVYIoVNMTAytW7dm//796mmyvOTk5MSwYcPo1q1bno8t3i/yCUkIIYQmSEMSQgihCXLKTgghhCbIJyQhhBCaIA1JCCGEJkhDEkIIoQnSkIQQQmiCNCQhhBCaIA1JCCGEJvwfK20HwkcqjBkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# province level\n",
    "fig = figure_bar(df = data_province_domestic, date_str = '2020-03-10', \n",
    "                 col = 'cum_confirmed', largestN = 0, log = True, figsize = (6, 8), fs = 16, \n",
    "                 title = 'China: provincial')\n",
    "fig = figure_bar(df = data_province_domestic, date_str = '2020-03-10', \n",
    "                 col = 'cum_cured', largestN = 0, log = True, figsize = (6, 8), fs = 16, \n",
    "                 title = 'China: provincial')\n",
    "fig = figure_bar(df = data_province_domestic, date_str = '2020-03-10', \n",
    "                 col = 'cum_dead', largestN = 0, log = True, figsize = (6, 8), fs = 16, \n",
    "                 title = 'China: provincial')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# city level\n",
    "#fig = figure_bar(data_city, '2020-03-10', col = 'cum_confirmed', groupby = 'province_name_en',title = 'National')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "#fig = figure_bar(data_city, '2020-03-10', col = 'new_confirmed', groupby = 'city_name_en', largestN = 10, title='Top 10 City')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# city level in Hubei province\n",
    "#fig = figure_bar(data_city[data_city['province_name_en'] == 'Hubei'], '2020-02-01', col = 'cum_dead', groupby = 'city_name_en', title = 'Hubei Province')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Compare the population size with the infection size\n",
    "# infection ratio (per mille)\n",
    "infection_ratio = [(name, round(data_province_domestic[(data_province_domestic.province_name_en == name) & (data_province_domestic.update_date <= date_tr)].cum_confirmed.max()/provincial_population_dict.get(name)*1e6, 3)) for name in names_province]\n",
    "# conclusion: in the SEIR model, S + E is approximately N\n",
    "# min(infection_ratio, key = lambda t: t[1]), max(infection_ratio, key = lambda t: t[1])\n",
    "infection_ratio = pd.DataFrame.from_records(infection_ratio, columns =['province_name_en', 'ratio']) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>province_name_en</th>\n",
       "      <th>ratio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Anhui</td>\n",
       "      <td>15.656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Beijing</td>\n",
       "      <td>19.265</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Chongqing</td>\n",
       "      <td>18.570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Fujian</td>\n",
       "      <td>7.511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Gansu</td>\n",
       "      <td>3.451</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Guangdong</td>\n",
       "      <td>11.925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Guangxi</td>\n",
       "      <td>5.116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Guizhou</td>\n",
       "      <td>4.056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Hainan</td>\n",
       "      <td>17.981</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Hebei</td>\n",
       "      <td>4.208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Heilongjiang</td>\n",
       "      <td>12.748</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Henan</td>\n",
       "      <td>13.243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Hubei</td>\n",
       "      <td>1145.175</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Hunan</td>\n",
       "      <td>14.756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Inner Mongolia</td>\n",
       "      <td>2.960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Jiangsu</td>\n",
       "      <td>7.838</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Jiangxi</td>\n",
       "      <td>20.118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Jilin</td>\n",
       "      <td>3.439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Liaoning</td>\n",
       "      <td>2.867</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Ningxia</td>\n",
       "      <td>10.899</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Qinghai</td>\n",
       "      <td>2.984</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Shaanxi</td>\n",
       "      <td>6.340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Shandong</td>\n",
       "      <td>7.544</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Shanghai</td>\n",
       "      <td>13.945</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Shanxi</td>\n",
       "      <td>3.577</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Sichuan</td>\n",
       "      <td>6.462</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Tianjin</td>\n",
       "      <td>8.720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Xinjiang</td>\n",
       "      <td>3.056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Yunnan</td>\n",
       "      <td>3.625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>21.161</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   province_name_en     ratio\n",
       "0             Anhui    15.656\n",
       "1           Beijing    19.265\n",
       "2         Chongqing    18.570\n",
       "3            Fujian     7.511\n",
       "4             Gansu     3.451\n",
       "5         Guangdong    11.925\n",
       "6           Guangxi     5.116\n",
       "7           Guizhou     4.056\n",
       "8            Hainan    17.981\n",
       "9             Hebei     4.208\n",
       "10     Heilongjiang    12.748\n",
       "11            Henan    13.243\n",
       "12            Hubei  1145.175\n",
       "13            Hunan    14.756\n",
       "14   Inner Mongolia     2.960\n",
       "15          Jiangsu     7.838\n",
       "16          Jiangxi    20.118\n",
       "17            Jilin     3.439\n",
       "18         Liaoning     2.867\n",
       "19          Ningxia    10.899\n",
       "20          Qinghai     2.984\n",
       "21          Shaanxi     6.340\n",
       "22         Shandong     7.544\n",
       "23         Shanghai    13.945\n",
       "24           Shanxi     3.577\n",
       "25          Sichuan     6.462\n",
       "26          Tianjin     8.720\n",
       "27         Xinjiang     3.056\n",
       "28           Yunnan     3.625\n",
       "29         Zhejiang    21.161"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "infection_ratio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# ir stands for infection ratio\n",
    "def figure_ir_bar(df, update_date_tr, largestN = 0, log = True, figsize = (12, 8), fs = 18, title = None):\n",
    "    \n",
    "    df_single = df[df['province_name_en'].isin(names_province)]\n",
    "    df_single = df_single.sort_values(by = 'ratio')\n",
    "    df_single = df_single.reset_index(drop = True)\n",
    "        \n",
    "    if largestN > 0:\n",
    "        df_single = df_single[-largestN:]  # only plot the first N bars\n",
    "    else:\n",
    "        largestN = df_single.shape[0]\n",
    "    \n",
    "    palette = plt.get_cmap('pink_r')\n",
    "    palette = tealrose\n",
    "    palette = list(itertools.chain.from_iterable(itertools.repeat(x, int(np.ceil(largestN/len(palette)))) for x in palette))\n",
    "    palette = palette[:largestN]\n",
    "    sns.set_style(\"whitegrid\")\n",
    "    fig = plt.figure(figsize = figsize)\n",
    "    ax = fig.add_subplot(111)\n",
    "    bars = df_single['ratio'].tolist()\n",
    "    names = df_single['province_name_en']\n",
    "    ax.barh(names, bars, color = palette, height = 0.4, alpha = 0.8) # palette(np.linspace(0.2, 0.8, largestN))\n",
    "    for j, v in enumerate(bars): # add text\n",
    "        ax.text(v*1.1, j - 0.2, str(round(v)), color = 'black', fontsize = fs - 6)\n",
    "    ax.set_xlabel(\"Infection rate (per million)\", fontsize = fs - 2)\n",
    "    ax.set_ylabel('Province', fontsize = fs - 2)\n",
    "    if log == True:\n",
    "        ax.set_xscale('log')\n",
    "        xmin = 1\n",
    "        xmax = 1e4\n",
    "        ax.set_xlim(xmin, xmax)\n",
    "        \n",
    "    \n",
    "    if title is not None:\n",
    "        fig.suptitle(title, fontsize = fs, y = 1.035)\n",
    "    plt.figtext(0.5, 1, update_date_tr.strftime(\"%d %B, %Y\"), ha = \"center\", va = \"top\", fontsize = fs - 4)\n",
    "    fig.savefig(_Figure_PATH_ + 'figures_china_be/' + 'China_infection_rate.png', dpi = 400, bbox_inches='tight')\n",
    "    return fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = figure_ir_bar(df = infection_ratio, update_date_tr = date_tr, largestN = 0, log = True, figsize = (6, 8), fs = 16, \n",
    "                    title = 'China: provincial infection rate')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# a dictionary for the pyecharts geo maps\n",
    "d = {'湖北': 'Hubei',\n",
    " '广东': 'Guangdong',\n",
    " '河南': 'Henan',\n",
    " '浙江': 'Zhejiang',\n",
    " '湖南': 'Hunan',\n",
    " '安徽': 'Anhui',\n",
    " '江西': 'Jiangxi',\n",
    " '山东': 'Shandong',\n",
    " '江苏': 'Jiangsu',\n",
    " '重庆': 'Chongqing',\n",
    " '四川': 'Sichuan',\n",
    " '黑龙江': 'Heilongjiang',\n",
    " '北京': 'Beijing',\n",
    " '上海': 'Shanghai',\n",
    " '河北': 'Hebei',\n",
    " '福建': 'Fujian',\n",
    " '广西': 'Guangxi',\n",
    " '陕西': 'Shaanxi',\n",
    " '云南': 'Yunnan',\n",
    " '海南': 'Hainan',\n",
    " '贵州': 'Guizhou',\n",
    " '天津': 'Tianjin',\n",
    " '山西': 'Shanxi',\n",
    " '辽宁': 'Liaoning',\n",
    " '吉林': 'Jilin',\n",
    " '甘肃': 'Gansu',\n",
    " '新疆': 'Xinjiang',\n",
    " '宁夏': 'Ningxia',\n",
    " '内蒙古': 'Inner Mongolia',\n",
    " '青海': 'Qinghai'}\n",
    "#for k, v in d.items():\n",
    "    #print ('if(params.name == \\'' + k + '\\')' + '\\n' + '    ' + \n",
    "                #'return \\'' + v + '\\' + \\' : \\' + ' + 'params.value[2];')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "metadata": {},
   "outputs": [],
   "source": [
    "# geo maps\n",
    "def figure_map_png(df, end_date, pieces, vr_upper = 0, fs = 20, subject = 'scatter'):\n",
    "    \n",
    "    data_single = df[df.update_date == end_date]\n",
    "    data_single = data_single.sort_values(by='cum_confirmed', ascending=False)\n",
    "    data_single = data_single.reset_index(drop=True)\n",
    "    # for the scatter plot or heatmap\n",
    "    provinces = data_single.province_name\n",
    "    provinces = [pyecharts_province_dict[temp] for temp in provinces]\n",
    "    values = data_single.cum_confirmed\n",
    "    fn = \"\"\"\n",
    "    function(params) {\n",
    "        return params.name + ' : ' + params.value[2]\n",
    "    }\n",
    "    \"\"\"\n",
    "    # show province names and values\n",
    "    fn = \"\"\"\n",
    "    function(params) {\n",
    "        if(params.name == '湖北')\n",
    "            return 'Hubei' + ' : ' + params.value[2];\n",
    "        if(params.name == '广东')\n",
    "            return 'Guangdong' + ' : ' + params.value[2];\n",
    "        if(params.name == '河南')\n",
    "            return 'Henan' + ' : ' + params.value[2];\n",
    "        if(params.name == '浙江')\n",
    "            return 'Zhejiang' + ' : ' + params.value[2];\n",
    "        if(params.name == '湖南')\n",
    "            return 'Hunan' + ' : ' + params.value[2];\n",
    "        if(params.name == '安徽')\n",
    "            return 'Anhui' + ' : ' + params.value[2];\n",
    "        if(params.name == '江西')\n",
    "            return 'Jiangxi' + ' : ' + params.value[2];\n",
    "        if(params.name == '山东')\n",
    "            return 'Shandong' + ' : ' + params.value[2];\n",
    "        if(params.name == '江苏')\n",
    "            return 'Jiangsu' + ' : ' + params.value[2];\n",
    "        if(params.name == '重庆')\n",
    "            return 'Chongqing' + ' : ' + params.value[2];\n",
    "        if(params.name == '四川')\n",
    "            return 'Sichuan' + ' : ' + params.value[2];\n",
    "        if(params.name == '黑龙江')\n",
    "            return 'Heilongjiang' + ' : ' + params.value[2];\n",
    "        if(params.name == '北京')\n",
    "            return 'Beijing' + ' : ' + params.value[2];\n",
    "        if(params.name == '上海')\n",
    "            return 'Shanghai' + ' : ' + params.value[2];\n",
    "        if(params.name == '河北')\n",
    "            return 'Hebei' + ' : ' + params.value[2];\n",
    "        if(params.name == '福建')\n",
    "            return 'Fujian' + ' : ' + params.value[2];\n",
    "        if(params.name == '广西')\n",
    "            return 'Guangxi' + ' : ' + params.value[2];\n",
    "        if(params.name == '陕西')\n",
    "            return 'Shaanxi' + ' : ' + params.value[2];\n",
    "        if(params.name == '云南')\n",
    "            return 'Yunnan' + ' : ' + params.value[2];\n",
    "        if(params.name == '海南')\n",
    "            return 'Hainan' + ' : ' + params.value[2];\n",
    "        if(params.name == '贵州')\n",
    "            return 'Guizhou' + ' : ' + params.value[2];\n",
    "        if(params.name == '天津')\n",
    "            return 'Tianjin' + ' : ' + params.value[2];\n",
    "        if(params.name == '山西')\n",
    "            return 'Shanxi' + ' : ' + params.value[2];\n",
    "        if(params.name == '辽宁')\n",
    "            return 'Liaoning' + ' : ' + params.value[2];\n",
    "        if(params.name == '吉林')\n",
    "            return 'Jilin' + ' : ' + params.value[2];\n",
    "        if(params.name == '甘肃')\n",
    "            return 'Gansu' + ' : ' + params.value[2];\n",
    "        if(params.name == '新疆')\n",
    "            return 'Xinjiang' + ' : ' + params.value[2];\n",
    "        if(params.name == '宁夏')\n",
    "            return 'Ningxia' + ' : ' + params.value[2];\n",
    "        if(params.name == '内蒙古')\n",
    "            return 'Inner Mongolia' + ' : ' + params.value[2];\n",
    "        if(params.name == '青海')\n",
    "            return 'Qinghai' + ' : ' + params.value[2];\n",
    "    }\n",
    "    \"\"\"\n",
    "    # show only province names\n",
    "    gn = \"\"\"\n",
    "    function(params) {\n",
    "        if(params.name == '湖北')\n",
    "            return 'Hubei';\n",
    "        if(params.name == '广东')\n",
    "            return 'Guangdong';\n",
    "        if(params.name == '河南')\n",
    "            return 'Henan';\n",
    "        if(params.name == '浙江')\n",
    "            return 'Zhejiang';\n",
    "        if(params.name == '湖南')\n",
    "            return 'Hunan';\n",
    "        if(params.name == '安徽')\n",
    "            return 'Anhui';\n",
    "        if(params.name == '江西')\n",
    "            return 'Jiangxi';\n",
    "        if(params.name == '山东')\n",
    "            return 'Shandong';\n",
    "        if(params.name == '江苏')\n",
    "            return 'Jiangsu';\n",
    "        if(params.name == '重庆')\n",
    "            return 'Chongqing';\n",
    "        if(params.name == '四川')\n",
    "            return 'Sichuan';\n",
    "        if(params.name == '黑龙江')\n",
    "            return 'Heilongjiang';\n",
    "        if(params.name == '北京')\n",
    "            return 'Beijing';\n",
    "        if(params.name == '上海')\n",
    "            return 'Shanghai';\n",
    "        if(params.name == '河北')\n",
    "            return 'Hebei';\n",
    "        if(params.name == '福建')\n",
    "            return 'Fujian';\n",
    "        if(params.name == '广西')\n",
    "            return 'Guangxi';\n",
    "        if(params.name == '陕西')\n",
    "            return 'Shaanxi';\n",
    "        if(params.name == '云南')\n",
    "            return 'Yunnan';\n",
    "        if(params.name == '海南')\n",
    "            return 'Hainan';\n",
    "        if(params.name == '贵州')\n",
    "            return 'Guizhou';\n",
    "        if(params.name == '天津')\n",
    "            return 'Tianjin';\n",
    "        if(params.name == '山西')\n",
    "            return 'Shanxi';\n",
    "        if(params.name == '辽宁')\n",
    "            return 'Liaoning';\n",
    "        if(params.name == '吉林')\n",
    "            return 'Jilin';\n",
    "        if(params.name == '甘肃')\n",
    "            return 'Gansu';\n",
    "        if(params.name == '新疆')\n",
    "            return 'Xinjiang';\n",
    "        if(params.name == '宁夏')\n",
    "            return 'Ningxia';\n",
    "        if(params.name == '内蒙古')\n",
    "            return 'Inner Mongolia';\n",
    "        if(params.name == '青海')\n",
    "            return 'Qinghai';\n",
    "    }\n",
    "    \"\"\"\n",
    "    # show only 5 province names and values\n",
    "    hn = \"\"\"\n",
    "    function(params) {\n",
    "        if(params.name == '湖北')\n",
    "            return 'Hubei' + ' : ' + params.value[2];\n",
    "        if(params.name == '广东')\n",
    "            return 'Guangdong' + ' : ' + params.value[2];\n",
    "        if(params.name == '河南')\n",
    "            return 'Henan' + ' : ' + params.value[2];\n",
    "        if(params.name == '浙江')\n",
    "            return 'Zhejiang' + ' : ' + params.value[2];\n",
    "        if(params.name == '湖南')\n",
    "            return 'Hunan' + ' : ' + params.value[2];\n",
    "        return '';\n",
    "    }\n",
    "    \"\"\"\n",
    "    # show only 5 province names\n",
    "    ln = \"\"\"\n",
    "    function(params) {\n",
    "        if(params.name == '湖北')\n",
    "            return 'Hubei';\n",
    "        if(params.name == '广东')\n",
    "            return 'Guangdong';\n",
    "        if(params.name == '河南')\n",
    "            return 'Henan';\n",
    "        if(params.name == '浙江')\n",
    "            return 'Zhejiang';\n",
    "        if(params.name == '湖南')\n",
    "            return 'Hunan';\n",
    "        return '';\n",
    "    }\n",
    "    \"\"\"\n",
    "    # scatter plot\n",
    "    if subject == 'scatter':\n",
    "        # show both province name and number of infected\n",
    "        \n",
    "        c = (\n",
    "                Geo(init_opts = opts.InitOpts(width = '900px', height = '600px', bg_color = \"#FFFFFF\"),)\n",
    "                .add_schema(maptype = \"china\", itemstyle_opts = opts.ItemStyleOpts(color = \"white\", border_color = \"black\"),)\n",
    "                .add(\n",
    "                    \"number of infected\",\n",
    "                    [list(z) for z in zip(provinces, values)],\n",
    "                    #type_= ChartType.EFFECT_SCATTER,\n",
    "                    color = '#d94e5d',\n",
    "                    symbol_size = 10,\n",
    "                    point_size = 5,\n",
    "                )\n",
    "                .set_series_opts(\n",
    "                    label_opts = opts.LabelOpts(\n",
    "                        formatter=JsCode(ln), font_size = fs - 3, color = 'black'))\n",
    "                #.set_series_opts(label_opts = opts.LabelOpts(is_show = True))\n",
    "                .set_global_opts(\n",
    "                    legend_opts = opts.LegendOpts(textstyle_opts = opts.TextStyleOpts(font_size = fs + 5)),\n",
    "                    visualmap_opts = opts.VisualMapOpts(\n",
    "                        is_show = True, split_number = 6, is_piecewise = True, pos_top = 'center',\n",
    "                        pieces = pieces, textstyle_opts = opts.TextStyleOpts(font_size = fs)),\n",
    "                    title_opts = opts.TitleOpts(title = \"China\", subtitle = end_date.strftime(\"%d %B, %Y\"),\n",
    "                                               title_textstyle_opts = opts.TextStyleOpts(font_size = fs + 10),\n",
    "                                               subtitle_textstyle_opts = opts.TextStyleOpts(font_size = fs)))\n",
    "            )\n",
    "        \n",
    "        make_snapshot(snapshot, c.render(_Figure_PATH_ + \"China_map.html\"), _Figure_PATH_ + \"China_map.png\")\n",
    "        return c\n",
    "    # heatmap plot\n",
    "    else:\n",
    "        c = (\n",
    "            Geo(init_opts = opts.InitOpts(width = '900px', height = '600px', bg_color = \"#FFFFFF\"))\n",
    "            .add_schema(maptype=\"china\", itemstyle_opts = opts.ItemStyleOpts(color = \"white\", border_color = \"black\"),)\n",
    "            .add(\n",
    "                    \"number of infected\",\n",
    "                    [list(z) for z in zip(provinces, values)],\n",
    "                    color = '#d94e5d',\n",
    "                    #type_= ChartType.EFFECT_SCATTER,\n",
    "                    symbol_size = 8,\n",
    "                    point_size = 5,\n",
    "                )\n",
    "            .add(\n",
    "                \"number of infected\",\n",
    "                [list(z) for z in zip(provinces, values)],\n",
    "                type_ = ChartType.HEATMAP,\n",
    "                symbol_size = 15,  \n",
    "            )\n",
    "            .set_series_opts(label_opts = opts.LabelOpts(\n",
    "                        formatter = JsCode(ln), font_size = fs - 3, color = 'black'))\n",
    "            .set_global_opts(\n",
    "                legend_opts = opts.LegendOpts(textstyle_opts = opts.TextStyleOpts(font_size = fs + 5)),\n",
    "                visualmap_opts = opts.VisualMapOpts(max_ = vr_upper, pos_top = 'center',\n",
    "                                                   textstyle_opts = opts.TextStyleOpts(font_size = fs)),\n",
    "                title_opts = opts.TitleOpts(title = \"China\",subtitle = end_date.strftime(\"%d %B, %Y\"),\n",
    "                                            title_textstyle_opts = opts.TextStyleOpts(font_size = fs + 10),\n",
    "                                            subtitle_textstyle_opts = opts.TextStyleOpts(font_size = fs + 5)))\n",
    "        )\n",
    "        c.render_notebook()\n",
    "        make_snapshot(snapshot, c.render(), _Figure_PATH_ + \"China_heatmap.png\")\n",
    "        return c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "metadata": {},
   "outputs": [],
   "source": [
    "end_date = datetime.date(int(2020),int(3),int(10))\n",
    "pieces = [{'min': 1001},  # no max for this\n",
    "              {'min': 501, 'max': 1000},\n",
    "              {'min': 201, 'max': 500},\n",
    "              {'min': 101, 'max': 200},\n",
    "              {'min': 51, 'max': 100},\n",
    "              {'min': 0, 'max': 50}]\n",
    "c = figure_map_png(data_province_domestic, end_date, pieces, fs = 18, subject = 'scatter')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 194,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<script>\n",
       "    require.config({\n",
       "        paths: {\n",
       "            'echarts':'https://assets.pyecharts.org/assets/echarts.min', 'china':'https://assets.pyecharts.org/assets/maps/china'\n",
       "        }\n",
       "    });\n",
       "</script>\n",
       "\n",
       "        <div id=\"5ae010c22a0644a7a50823152b5dd8d2\" style=\"width:900px; height:600px;\"></div>\n",
       "\n",
       "<script>\n",
       "        require(['echarts', 'china'], function(echarts) {\n",
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       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
       "    \"animationDelay\": 0,\n",
       "    \"animationDurationUpdate\": 300,\n",
       "    \"animationEasingUpdate\": \"cubicOut\",\n",
       "    \"animationDelayUpdate\": 0,\n",
       "    \"color\": [\n",
       "        \"#d94e5d\",\n",
       "        \"#c23531\",\n",
       "        \"#2f4554\",\n",
       "        \"#61a0a8\",\n",
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       "            \"label\": {\n",
       "                \"show\": true,\n",
       "                \"position\": \"top\",\n",
       "                \"color\": \"black\",\n",
       "                \"margin\": 8,\n",
       "                \"fontSize\": 13,\n",
       "                \"formatter\":     function(params) {        if(params.name == '\\u6e56\\u5317')            return 'Hubei';        if(params.name == '\\u5e7f\\u4e1c')            return 'Guangdong';        if(params.name == '\\u6cb3\\u5357')            return 'Henan';        if(params.name == '\\u6d59\\u6c5f')            return 'Zhejiang';        if(params.name == '\\u6e56\\u5357')            return 'Hunan';        return '';    }    \n",
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       "        {\n",
       "            \"type\": \"heatmap\",\n",
       "            \"name\": \"number of infected\",\n",
       "            \"coordinateSystem\": \"geo\",\n",
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       "                    \"value\": [\n",
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       "                    ]\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u5185\\u8499\\u53e4\",\n",
       "                    \"value\": [\n",
       "                        111.765617,\n",
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       "                        75.0\n",
       "                    ]\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u9752\\u6d77\",\n",
       "                    \"value\": [\n",
       "                        101.780199,\n",
       "                        36.620901,\n",
       "                        18.0\n",
       "                    ]\n",
       "                }\n",
       "            ],\n",
       "            \"pointSize\": 20,\n",
       "            \"blurSize\": 20,\n",
       "            \"label\": {\n",
       "                \"show\": true,\n",
       "                \"position\": \"top\",\n",
       "                \"color\": \"black\",\n",
       "                \"margin\": 8,\n",
       "                \"fontSize\": 13,\n",
       "                \"formatter\":     function(params) {        if(params.name == '\\u6e56\\u5317')            return 'Hubei';        if(params.name == '\\u5e7f\\u4e1c')            return 'Guangdong';        if(params.name == '\\u6cb3\\u5357')            return 'Henan';        if(params.name == '\\u6d59\\u6c5f')            return 'Zhejiang';        if(params.name == '\\u6e56\\u5357')            return 'Hunan';        return '';    }    \n",
       "            },\n",
       "            \"rippleEffect\": {\n",
       "                \"show\": true,\n",
       "                \"brushType\": \"stroke\",\n",
       "                \"scale\": 2.5,\n",
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       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"legend\": [\n",
       "        {\n",
       "            \"data\": [\n",
       "                \"number of infected\",\n",
       "                \"number of infected\"\n",
       "            ],\n",
       "            \"selected\": {\n",
       "                \"number of infected\": true\n",
       "            },\n",
       "            \"show\": true,\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10,\n",
       "            \"itemWidth\": 25,\n",
       "            \"itemHeight\": 14,\n",
       "            \"textStyle\": {\n",
       "                \"fontSize\": 21\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"formatter\": function (params) {        return params.name + ' : ' + params.value[2];    },\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0\n",
       "    },\n",
       "    \"title\": [\n",
       "        {\n",
       "            \"text\": \"China\",\n",
       "            \"subtext\": \"10 March, 2020\",\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10,\n",
       "            \"textStyle\": {\n",
       "                \"fontSize\": 26\n",
       "            },\n",
       "            \"subtextStyle\": {\n",
       "                \"fontSize\": 21\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"visualMap\": {\n",
       "        \"show\": true,\n",
       "        \"type\": \"continuous\",\n",
       "        \"min\": 0,\n",
       "        \"max\": 1000,\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 16\n",
       "        },\n",
       "        \"inRange\": {\n",
       "            \"color\": [\n",
       "                \"#50a3ba\",\n",
       "                \"#eac763\",\n",
       "                \"#d94e5d\"\n",
       "            ]\n",
       "        },\n",
       "        \"calculable\": true,\n",
       "        \"inverse\": false,\n",
       "        \"splitNumber\": 5,\n",
       "        \"orient\": \"vertical\",\n",
       "        \"top\": \"center\",\n",
       "        \"showLabel\": true,\n",
       "        \"itemWidth\": 20,\n",
       "        \"itemHeight\": 140,\n",
       "        \"borderWidth\": 0\n",
       "    },\n",
       "    \"geo\": {\n",
       "        \"map\": \"china\",\n",
       "        \"roam\": true,\n",
       "        \"itemStyle\": {\n",
       "            \"color\": \"white\",\n",
       "            \"borderColor\": \"black\"\n",
       "        },\n",
       "        \"emphasis\": {}\n",
       "    }\n",
       "};\n",
       "                chart_5ae010c22a0644a7a50823152b5dd8d2.setOption(option_5ae010c22a0644a7a50823152b5dd8d2);\n",
       "        });\n",
       "    </script>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x7fa268a8fdd8>"
      ]
     },
     "execution_count": 194,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vr_upper = 1000\n",
    "c = figure_map_png(data_province_domestic, end_date, pieces, vr_upper, fs = 16, subject = 'heatmap')\n",
    "c.render_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 195,
   "metadata": {},
   "outputs": [],
   "source": [
    "# geo maps\n",
    "def figure_map_html(df, end_date, pieces, vr_upper = 0, fs = 20, subject = 'scatter'):\n",
    "    \n",
    "    data_single = df[df.update_date == end_date]\n",
    "    data_single = data_single.sort_values(by='cum_confirmed', ascending=False)\n",
    "    data_single = data_single.reset_index(drop=True)\n",
    "    # for the scatter plot or heatmap\n",
    "    provinces = data_single.province_name\n",
    "    provinces = [pyecharts_province_dict[temp] for temp in provinces]\n",
    "    values = data_single.cum_confirmed\n",
    "    fn = \"\"\"\n",
    "    function(params) {\n",
    "        return params.name + ' : ' + params.value[2]\n",
    "    }\n",
    "    \"\"\"\n",
    "    # show province names and values\n",
    "    fn = \"\"\"\n",
    "    function(params) {\n",
    "        if(params.name == '湖北')\n",
    "            return 'Hubei' + ' : ' + params.value[2];\n",
    "        if(params.name == '广东')\n",
    "            return 'Guangdong' + ' : ' + params.value[2];\n",
    "        if(params.name == '河南')\n",
    "            return 'Henan' + ' : ' + params.value[2];\n",
    "        if(params.name == '浙江')\n",
    "            return 'Zhejiang' + ' : ' + params.value[2];\n",
    "        if(params.name == '湖南')\n",
    "            return 'Hunan' + ' : ' + params.value[2];\n",
    "        if(params.name == '安徽')\n",
    "            return 'Anhui' + ' : ' + params.value[2];\n",
    "        if(params.name == '江西')\n",
    "            return 'Jiangxi' + ' : ' + params.value[2];\n",
    "        if(params.name == '山东')\n",
    "            return 'Shandong' + ' : ' + params.value[2];\n",
    "        if(params.name == '江苏')\n",
    "            return 'Jiangsu' + ' : ' + params.value[2];\n",
    "        if(params.name == '重庆')\n",
    "            return 'Chongqing' + ' : ' + params.value[2];\n",
    "        if(params.name == '四川')\n",
    "            return 'Sichuan' + ' : ' + params.value[2];\n",
    "        if(params.name == '黑龙江')\n",
    "            return 'Heilongjiang' + ' : ' + params.value[2];\n",
    "        if(params.name == '北京')\n",
    "            return 'Beijing' + ' : ' + params.value[2];\n",
    "        if(params.name == '上海')\n",
    "            return 'Shanghai' + ' : ' + params.value[2];\n",
    "        if(params.name == '河北')\n",
    "            return 'Hebei' + ' : ' + params.value[2];\n",
    "        if(params.name == '福建')\n",
    "            return 'Fujian' + ' : ' + params.value[2];\n",
    "        if(params.name == '广西')\n",
    "            return 'Guangxi' + ' : ' + params.value[2];\n",
    "        if(params.name == '陕西')\n",
    "            return 'Shaanxi' + ' : ' + params.value[2];\n",
    "        if(params.name == '云南')\n",
    "            return 'Yunnan' + ' : ' + params.value[2];\n",
    "        if(params.name == '海南')\n",
    "            return 'Hainan' + ' : ' + params.value[2];\n",
    "        if(params.name == '贵州')\n",
    "            return 'Guizhou' + ' : ' + params.value[2];\n",
    "        if(params.name == '天津')\n",
    "            return 'Tianjin' + ' : ' + params.value[2];\n",
    "        if(params.name == '山西')\n",
    "            return 'Shanxi' + ' : ' + params.value[2];\n",
    "        if(params.name == '辽宁')\n",
    "            return 'Liaoning' + ' : ' + params.value[2];\n",
    "        if(params.name == '吉林')\n",
    "            return 'Jilin' + ' : ' + params.value[2];\n",
    "        if(params.name == '甘肃')\n",
    "            return 'Gansu' + ' : ' + params.value[2];\n",
    "        if(params.name == '新疆')\n",
    "            return 'Xinjiang' + ' : ' + params.value[2];\n",
    "        if(params.name == '宁夏')\n",
    "            return 'Ningxia' + ' : ' + params.value[2];\n",
    "        if(params.name == '内蒙古')\n",
    "            return 'Inner Mongolia' + ' : ' + params.value[2];\n",
    "        if(params.name == '青海')\n",
    "            return 'Qinghai' + ' : ' + params.value[2];\n",
    "    }\n",
    "    \"\"\"\n",
    "    # show only province names\n",
    "    gn = \"\"\"\n",
    "    function(params) {\n",
    "        if(params.name == '湖北')\n",
    "            return 'Hubei';\n",
    "        if(params.name == '广东')\n",
    "            return 'Guangdong';\n",
    "        if(params.name == '河南')\n",
    "            return 'Henan';\n",
    "        if(params.name == '浙江')\n",
    "            return 'Zhejiang';\n",
    "        if(params.name == '湖南')\n",
    "            return 'Hunan';\n",
    "        if(params.name == '安徽')\n",
    "            return 'Anhui';\n",
    "        if(params.name == '江西')\n",
    "            return 'Jiangxi';\n",
    "        if(params.name == '山东')\n",
    "            return 'Shandong';\n",
    "        if(params.name == '江苏')\n",
    "            return 'Jiangsu';\n",
    "        if(params.name == '重庆')\n",
    "            return 'Chongqing';\n",
    "        if(params.name == '四川')\n",
    "            return 'Sichuan';\n",
    "        if(params.name == '黑龙江')\n",
    "            return 'Heilongjiang';\n",
    "        if(params.name == '北京')\n",
    "            return 'Beijing';\n",
    "        if(params.name == '上海')\n",
    "            return 'Shanghai';\n",
    "        if(params.name == '河北')\n",
    "            return 'Hebei';\n",
    "        if(params.name == '福建')\n",
    "            return 'Fujian';\n",
    "        if(params.name == '广西')\n",
    "            return 'Guangxi';\n",
    "        if(params.name == '陕西')\n",
    "            return 'Shaanxi';\n",
    "        if(params.name == '云南')\n",
    "            return 'Yunnan';\n",
    "        if(params.name == '海南')\n",
    "            return 'Hainan';\n",
    "        if(params.name == '贵州')\n",
    "            return 'Guizhou';\n",
    "        if(params.name == '天津')\n",
    "            return 'Tianjin';\n",
    "        if(params.name == '山西')\n",
    "            return 'Shanxi';\n",
    "        if(params.name == '辽宁')\n",
    "            return 'Liaoning';\n",
    "        if(params.name == '吉林')\n",
    "            return 'Jilin';\n",
    "        if(params.name == '甘肃')\n",
    "            return 'Gansu';\n",
    "        if(params.name == '新疆')\n",
    "            return 'Xinjiang';\n",
    "        if(params.name == '宁夏')\n",
    "            return 'Ningxia';\n",
    "        if(params.name == '内蒙古')\n",
    "            return 'Inner Mongolia';\n",
    "        if(params.name == '青海')\n",
    "            return 'Qinghai';\n",
    "    }\n",
    "    \"\"\"\n",
    "    # show only 5 province names and values\n",
    "    hn = \"\"\"\n",
    "    function(params) {\n",
    "        if(params.name == '湖北')\n",
    "            return 'Hubei' + ' : ' + params.value[2];\n",
    "        if(params.name == '广东')\n",
    "            return 'Guangdong' + ' : ' + params.value[2];\n",
    "        if(params.name == '河南')\n",
    "            return 'Henan' + ' : ' + params.value[2];\n",
    "        if(params.name == '浙江')\n",
    "            return 'Zhejiang' + ' : ' + params.value[2];\n",
    "        if(params.name == '湖南')\n",
    "            return 'Hunan' + ' : ' + params.value[2];\n",
    "        return '';\n",
    "    }\n",
    "    \"\"\"\n",
    "    # show only 5 province names\n",
    "    ln = \"\"\"\n",
    "    function(params) {\n",
    "        if(params.name == '湖北')\n",
    "            return 'Hubei';\n",
    "        if(params.name == '广东')\n",
    "            return 'Guangdong';\n",
    "        if(params.name == '河南')\n",
    "            return 'Henan';\n",
    "        if(params.name == '浙江')\n",
    "            return 'Zhejiang';\n",
    "        if(params.name == '湖南')\n",
    "            return 'Hunan';\n",
    "        return '';\n",
    "    }\n",
    "    \"\"\"\n",
    "    # scatter plot\n",
    "    if subject == 'scatter':\n",
    "        # show both province name and number of infected\n",
    "        \n",
    "        c = (\n",
    "                Geo(init_opts = opts.InitOpts(width = '750px', height = '500px', bg_color = \"#FFFFFF\"),)\n",
    "                .add_schema(maptype = \"china\", itemstyle_opts = opts.ItemStyleOpts(color = \"white\", border_color = \"black\"),)\n",
    "                .add(\n",
    "                    \"number of infected\",\n",
    "                    [list(z) for z in zip(provinces, values)],\n",
    "                    #type_= ChartType.EFFECT_SCATTER,\n",
    "                    color = '#d94e5d',\n",
    "                    symbol_size = 10,\n",
    "                    point_size = 5,\n",
    "                )\n",
    "                .set_series_opts(\n",
    "                    label_opts = opts.LabelOpts(\n",
    "                        formatter=JsCode(ln), font_size = fs - 3, color = 'black'))\n",
    "                #.set_series_opts(label_opts = opts.LabelOpts(is_show = True))\n",
    "                .set_global_opts(\n",
    "                    legend_opts = opts.LegendOpts(textstyle_opts = opts.TextStyleOpts(font_size = fs),\n",
    "                                                 item_width = 20, item_height = 10,),\n",
    "                    visualmap_opts = opts.VisualMapOpts(\n",
    "                        is_show = True, split_number = 6, is_piecewise = True, pos_top = 'center',\n",
    "                        pieces = pieces, textstyle_opts = opts.TextStyleOpts(font_size = fs),\n",
    "                        item_width = 20, item_height = 10),\n",
    "                    title_opts = opts.TitleOpts(title = \"China\", subtitle = end_date.strftime(\"%d %B, %Y\"),\n",
    "                                               title_textstyle_opts = opts.TextStyleOpts(font_size = fs + 5),\n",
    "                                               subtitle_textstyle_opts = opts.TextStyleOpts(font_size = fs + 2)))\n",
    "            )\n",
    "        c.render(_Figure_PATH_ + \"China_map.html\")\n",
    "        return c\n",
    "    # heatmap plot\n",
    "    else:\n",
    "        c = (\n",
    "            Geo(init_opts = opts.InitOpts(width = '750px', height = '500px', bg_color = \"#FFFFFF\"))\n",
    "            .add_schema(maptype=\"china\", itemstyle_opts = opts.ItemStyleOpts(color = \"white\", border_color = \"black\"),)\n",
    "            .add(\n",
    "                    \"number of infected\",\n",
    "                    [list(z) for z in zip(provinces, values)],\n",
    "                    color = '#d94e5d',\n",
    "                    #type_= ChartType.EFFECT_SCATTER,\n",
    "                    symbol_size = 6,\n",
    "                    point_size = 5,\n",
    "                )\n",
    "            .add(\n",
    "                \"number of infected\",\n",
    "                [list(z) for z in zip(provinces, values)],\n",
    "                type_ = ChartType.HEATMAP,\n",
    "                symbol_size = 15,  \n",
    "            )\n",
    "            .set_series_opts(label_opts = opts.LabelOpts(\n",
    "                        formatter=JsCode(ln), font_size = fs - 3, color = 'black'))\n",
    "            .set_global_opts(\n",
    "                legend_opts = opts.LegendOpts(textstyle_opts = opts.TextStyleOpts(font_size = fs),\n",
    "                                              item_width = 20, item_height = 10,),\n",
    "                visualmap_opts = opts.VisualMapOpts(max_ = vr_upper, pos_top = 'center',\n",
    "                                                    textstyle_opts = opts.TextStyleOpts(font_size = fs),\n",
    "                                                    item_width = 12, item_height = 100),\n",
    "                title_opts = opts.TitleOpts(title=\"China\",subtitle = end_date.strftime(\"%d %B, %Y\"),\n",
    "                                            title_textstyle_opts = opts.TextStyleOpts(font_size = fs + 5),\n",
    "                                            subtitle_textstyle_opts = opts.TextStyleOpts(font_size = fs + 2)))\n",
    "        )\n",
    "        c.render(_Figure_PATH_ + \"China_heatmap.html\")\n",
    "        return c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "metadata": {},
   "outputs": [],
   "source": [
    "c = figure_map_html(data_province_domestic, end_date, pieces, fs = 15, subject = 'scatter')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<script>\n",
       "    require.config({\n",
       "        paths: {\n",
       "            'echarts':'https://assets.pyecharts.org/assets/echarts.min', 'china':'https://assets.pyecharts.org/assets/maps/china'\n",
       "        }\n",
       "    });\n",
       "</script>\n",
       "\n",
       "        <div id=\"eadc04eb65b048188ebda2cf3a1f1bdc\" style=\"width:750px; height:500px;\"></div>\n",
       "\n",
       "<script>\n",
       "        require(['echarts', 'china'], function(echarts) {\n",
       "                var chart_eadc04eb65b048188ebda2cf3a1f1bdc = echarts.init(\n",
       "                    document.getElementById('eadc04eb65b048188ebda2cf3a1f1bdc'), 'white', {renderer: 'canvas'});\n",
       "                var option_eadc04eb65b048188ebda2cf3a1f1bdc = {\n",
       "    \"backgroundColor\": \"#FFFFFF\",\n",
       "    \"animation\": true,\n",
       "    \"animationThreshold\": 2000,\n",
       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
       "    \"animationDelay\": 0,\n",
       "    \"animationDurationUpdate\": 300,\n",
       "    \"animationEasingUpdate\": \"cubicOut\",\n",
       "    \"animationDelayUpdate\": 0,\n",
       "    \"color\": [\n",
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       "                }\n",
       "            ],\n",
       "            \"label\": {\n",
       "                \"show\": true,\n",
       "                \"position\": \"top\",\n",
       "                \"color\": \"black\",\n",
       "                \"margin\": 8,\n",
       "                \"fontSize\": 12,\n",
       "                \"formatter\":     function(params) {        if(params.name == '\\u6e56\\u5317')            return 'Hubei';        if(params.name == '\\u5e7f\\u4e1c')            return 'Guangdong';        if(params.name == '\\u6cb3\\u5357')            return 'Henan';        if(params.name == '\\u6d59\\u6c5f')            return 'Zhejiang';        if(params.name == '\\u6e56\\u5357')            return 'Hunan';        return '';    }    \n",
       "            },\n",
       "            \"rippleEffect\": {\n",
       "                \"show\": true,\n",
       "                \"brushType\": \"stroke\",\n",
       "                \"scale\": 2.5,\n",
       "                \"period\": 4\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"legend\": [\n",
       "        {\n",
       "            \"data\": [\n",
       "                \"number of infected\"\n",
       "            ],\n",
       "            \"selected\": {\n",
       "                \"number of infected\": true\n",
       "            },\n",
       "            \"show\": true,\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10,\n",
       "            \"itemWidth\": 20,\n",
       "            \"itemHeight\": 10,\n",
       "            \"textStyle\": {\n",
       "                \"fontSize\": 15\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"formatter\": function (params) {        return params.name + ' : ' + params.value[2];    },\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0\n",
       "    },\n",
       "    \"title\": [\n",
       "        {\n",
       "            \"text\": \"China\",\n",
       "            \"subtext\": \"10 March, 2020\",\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10,\n",
       "            \"textStyle\": {\n",
       "                \"fontSize\": 20\n",
       "            },\n",
       "            \"subtextStyle\": {\n",
       "                \"fontSize\": 17\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"visualMap\": {\n",
       "        \"show\": true,\n",
       "        \"type\": \"piecewise\",\n",
       "        \"min\": 0,\n",
       "        \"max\": 100,\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 15\n",
       "        },\n",
       "        \"inRange\": {\n",
       "            \"color\": [\n",
       "                \"#50a3ba\",\n",
       "                \"#eac763\",\n",
       "                \"#d94e5d\"\n",
       "            ]\n",
       "        },\n",
       "        \"calculable\": true,\n",
       "        \"inverse\": false,\n",
       "        \"splitNumber\": 6,\n",
       "        \"orient\": \"vertical\",\n",
       "        \"top\": \"center\",\n",
       "        \"showLabel\": true,\n",
       "        \"itemWidth\": 20,\n",
       "        \"itemHeight\": 10,\n",
       "        \"borderWidth\": 0,\n",
       "        \"pieces\": [\n",
       "            {\n",
       "                \"min\": 1001\n",
       "            },\n",
       "            {\n",
       "                \"min\": 501,\n",
       "                \"max\": 1000\n",
       "            },\n",
       "            {\n",
       "                \"min\": 201,\n",
       "                \"max\": 500\n",
       "            },\n",
       "            {\n",
       "                \"min\": 101,\n",
       "                \"max\": 200\n",
       "            },\n",
       "            {\n",
       "                \"min\": 51,\n",
       "                \"max\": 100\n",
       "            },\n",
       "            {\n",
       "                \"min\": 0,\n",
       "                \"max\": 50\n",
       "            }\n",
       "        ]\n",
       "    },\n",
       "    \"geo\": {\n",
       "        \"map\": \"china\",\n",
       "        \"roam\": true,\n",
       "        \"itemStyle\": {\n",
       "            \"color\": \"white\",\n",
       "            \"borderColor\": \"black\"\n",
       "        },\n",
       "        \"emphasis\": {}\n",
       "    }\n",
       "};\n",
       "                chart_eadc04eb65b048188ebda2cf3a1f1bdc.setOption(option_eadc04eb65b048188ebda2cf3a1f1bdc);\n",
       "        });\n",
       "    </script>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x7fa268b68630>"
      ]
     },
     "execution_count": 184,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c.render_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<script>\n",
       "    require.config({\n",
       "        paths: {\n",
       "            'echarts':'https://assets.pyecharts.org/assets/echarts.min', 'china':'https://assets.pyecharts.org/assets/maps/china'\n",
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       "\n",
       "        <div id=\"789a48642f054c288fa95cefa2b9f807\" style=\"width:750px; height:500px;\"></div>\n",
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     },
     "execution_count": 196,
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   ],
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    "vr_upper = 1000\n",
    "c = figure_map_html(data_province_domestic, end_date, pieces, vr_upper, fs = 15, subject = 'heatmap')\n",
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